vendor/libc++/libc++-release_39-r276489

82 files changed, 3355 insertions, 3205 deletions

diff --git a/test/std/numerics/c.math/cmath.pass.cpp b/test/std/numerics/c.math/cmath.pass.cpp
index 0b0d86288737..7161bd37e3e2 100644
--- a/test/std/numerics/c.math/cmath.pass.cpp
+++ b/test/std/numerics/c.math/cmath.pass.cpp
@@ -9,13 +9,11 @@
 
 // <cmath>
 
-// NOTE: isinf and isnan are tested separately because they are expected to fail
-// on linux. We don't want their expected failure to hide other failures in this file.
-
 #include <cmath>
 #include <type_traits>
 #include <cassert>
 
+#include "test_macros.h"
 #include "hexfloat.h"
 
 // convertible to int/float/double/etc
@@ -79,6 +77,7 @@ Ambiguous fma(Ambiguous, Ambiguous, Ambiguous){ return Ambiguous(); }
 Ambiguous fmax(Ambiguous, Ambiguous){ return Ambiguous(); }
 Ambiguous fmin(Ambiguous, Ambiguous){ return Ambiguous(); }
 Ambiguous hypot(Ambiguous, Ambiguous){ return Ambiguous(); }
+Ambiguous hypot(Ambiguous, Ambiguous, Ambiguous){ return Ambiguous(); }
 Ambiguous ilogb(Ambiguous){ return Ambiguous(); }
 Ambiguous lgamma(Ambiguous){ return Ambiguous(); }
 Ambiguous llrint(Ambiguous){ return Ambiguous(); }
@@ -631,6 +630,29 @@ void test_isgreaterequal()
     assert(std::isgreaterequal(-1.0, 0.F) == false);
 }
 
+void test_isinf()
+{
+#ifdef isinf
+#error isinf defined
+#endif
+    static_assert((std::is_same<decltype(std::isinf((float)0)), bool>::value), "");
+
+    typedef decltype(std::isinf((double)0)) DoubleRetType;
+#ifndef __linux__
+    static_assert((std::is_same<DoubleRetType, bool>::value), "");
+#else
+    // GLIBC < 2.26 defines 'isinf(double)' with a return type of 'int' in
+    // all C++ dialects. The test should tolerate this.
+    // See: https://sourceware.org/bugzilla/show_bug.cgi?id=19439
+    static_assert((std::is_same<DoubleRetType, bool>::value
+                || std::is_same<DoubleRetType, int>::value), "");
+#endif
+
+    static_assert((std::is_same<decltype(std::isinf(0)), bool>::value), "");
+    static_assert((std::is_same<decltype(std::isinf((long double)0)), bool>::value), "");
+    assert(std::isinf(-1.0) == false);
+}
+
 void test_isless()
 {
 #ifdef isless
@@ -688,6 +710,29 @@ void test_islessgreater()
     assert(std::islessgreater(-1.0, 0.F) == true);
 }
 
+void test_isnan()
+{
+#ifdef isnan
+#error isnan defined
+#endif
+    static_assert((std::is_same<decltype(std::isnan((float)0)), bool>::value), "");
+
+    typedef decltype(std::isnan((double)0)) DoubleRetType;
+#ifndef __linux__
+    static_assert((std::is_same<DoubleRetType, bool>::value), "");
+#else
+    // GLIBC < 2.26 defines 'isnan(double)' with a return type of 'int' in
+    // all C++ dialects. The test should tolerate this.
+    // See: https://sourceware.org/bugzilla/show_bug.cgi?id=19439
+    static_assert((std::is_same<DoubleRetType, bool>::value
+                || std::is_same<DoubleRetType, int>::value), "");
+#endif
+
+    static_assert((std::is_same<decltype(std::isnan(0)), bool>::value), "");
+    static_assert((std::is_same<decltype(std::isnan((long double)0)), bool>::value), "");
+    assert(std::isnan(-1.0) == false);
+}
+
 void test_isunordered()
 {
 #ifdef isunordered
@@ -1010,6 +1055,28 @@ void test_hypot()
     static_assert((std::is_same<decltype(std::hypot((int)0, (int)0)), double>::value), "");
     static_assert((std::is_same<decltype(hypot(Ambiguous(), Ambiguous())), Ambiguous>::value), "");
     assert(std::hypot(3,4) == 5);
+
+#if TEST_STD_VER > 14
+    static_assert((std::is_same<decltype(std::hypot((float)0, (float)0, (float)0)), float>::value), "");
+    static_assert((std::is_same<decltype(std::hypot((float)0, (bool)0, (float)0)), double>::value), "");
+    static_assert((std::is_same<decltype(std::hypot((float)0, (unsigned short)0, (double)0)), double>::value), "");
+    static_assert((std::is_same<decltype(std::hypot((float)0, (int)0, (long double)0)), long double>::value), "");
+    static_assert((std::is_same<decltype(std::hypot((float)0, (unsigned int)0)), double>::value), "");
+    static_assert((std::is_same<decltype(std::hypot((float)0, (double)0, (long)0)), double>::value), "");
+    static_assert((std::is_same<decltype(std::hypot((float)0, (long double)0, (unsigned long)0)), long double>::value), "");
+    static_assert((std::is_same<decltype(std::hypot((float)0, (int)0, (long long)0)), double>::value), "");
+    static_assert((std::is_same<decltype(std::hypot((float)0, (int)0, (unsigned long long)0)), double>::value), "");
+    static_assert((std::is_same<decltype(std::hypot((float)0, (double)0, (double)0)), double>::value), "");
+    static_assert((std::is_same<decltype(std::hypot((float)0, (long double)0, (long double)0)), long double>::value), "");
+    static_assert((std::is_same<decltype(std::hypot((float)0, (float)0, (double)0)), double>::value), "");
+    static_assert((std::is_same<decltype(std::hypot((float)0, (float)0, (long double)0)), long double>::value), "");
+    static_assert((std::is_same<decltype(std::hypot((float)0, (double)0, (long double)0)), long double>::value), "");
+    static_assert((std::is_same<decltype(std::hypot((int)0, (int)0, (int)0)), double>::value), "");
+    static_assert((std::is_same<decltype(hypot(Ambiguous(), Ambiguous(), Ambiguous())), Ambiguous>::value), "");
+
+    assert(std::hypot(2,3,6) == 7);
+    assert(std::hypot(1,4,8) == 9);
+#endif
 }
 
 void test_ilogb()
@@ -1443,9 +1510,11 @@ int main()
     test_isnormal();
     test_isgreater();
     test_isgreaterequal();
+    test_isinf();
     test_isless();
     test_islessequal();
     test_islessgreater();
+    test_isnan();
     test_isunordered();
     test_acosh();
     test_asinh();
diff --git a/test/std/numerics/c.math/cmath_isinf.pass.cpp b/test/std/numerics/c.math/cmath_isinf.pass.cpp
deleted file mode 100644
index 6cde04d9bc86..000000000000
--- a/test/std/numerics/c.math/cmath_isinf.pass.cpp
+++ /dev/null
@@ -1,30 +0,0 @@
-//===----------------------------------------------------------------------===//
-//
-//                     The LLVM Compiler Infrastructure
-//
-// This file is dual licensed under the MIT and the University of Illinois Open
-// Source Licenses. See LICENSE.TXT for details.
-//
-//===----------------------------------------------------------------------===//
-
-// <cmath>
-
-// isinf
-
-// XFAIL: linux
-
-#include <cmath>
-#include <type_traits>
-#include <cassert>
-
-int main()
-{
-#ifdef isinf
-#error isinf defined
-#endif
-    static_assert((std::is_same<decltype(std::isinf((float)0)), bool>::value), "");
-    static_assert((std::is_same<decltype(std::isinf((double)0)), bool>::value), "");
-    static_assert((std::is_same<decltype(std::isinf(0)), bool>::value), "");
-    static_assert((std::is_same<decltype(std::isinf((long double)0)), bool>::value), "");
-    assert(std::isinf(-1.0) == false);
-}
\ No newline at end of file
diff --git a/test/std/numerics/c.math/cmath_isnan.pass.cpp b/test/std/numerics/c.math/cmath_isnan.pass.cpp
deleted file mode 100644
index 7b33b9647052..000000000000
--- a/test/std/numerics/c.math/cmath_isnan.pass.cpp
+++ /dev/null
@@ -1,30 +0,0 @@
-//===----------------------------------------------------------------------===//
-//
-//                     The LLVM Compiler Infrastructure
-//
-// This file is dual licensed under the MIT and the University of Illinois Open
-// Source Licenses. See LICENSE.TXT for details.
-//
-//===----------------------------------------------------------------------===//
-
-// <cmath>
-
-// isnan
-
-// XFAIL: linux
-
-#include <cmath>
-#include <type_traits>
-#include <cassert>
-
-int main()
-{
-#ifdef isnan
-#error isnan defined
-#endif
-    static_assert((std::is_same<decltype(std::isnan((float)0)), bool>::value), "");
-    static_assert((std::is_same<decltype(std::isnan((double)0)), bool>::value), "");
-    static_assert((std::is_same<decltype(std::isnan(0)), bool>::value), "");
-    static_assert((std::is_same<decltype(std::isnan((long double)0)), bool>::value), "");
-    assert(std::isnan(-1.0) == false);
-}
diff --git a/test/std/numerics/cfenv/cfenv.syn/cfenv.pass.cpp b/test/std/numerics/cfenv/cfenv.syn/cfenv.pass.cpp
index fcf075a36e1a..f2bf6433ceb4 100644
--- a/test/std/numerics/cfenv/cfenv.syn/cfenv.pass.cpp
+++ b/test/std/numerics/cfenv/cfenv.syn/cfenv.pass.cpp
@@ -62,6 +62,8 @@ int main()
 {
     std::fenv_t fenv;
     std::fexcept_t fex;
+    ((void)fenv); // Prevent unused warning
+    ((void)fex); // Prevent unused warning
     static_assert((std::is_same<decltype(std::feclearexcept(0)), int>::value), "");
     static_assert((std::is_same<decltype(std::fegetexceptflag(&fex, 0)), int>::value), "");
     static_assert((std::is_same<decltype(std::feraiseexcept(0)), int>::value), "");
diff --git a/test/std/numerics/cfenv/version.pass.cpp b/test/std/numerics/cfenv/version.pass.cpp
deleted file mode 100644
index 727d5bdf3994..000000000000
--- a/test/std/numerics/cfenv/version.pass.cpp
+++ /dev/null
@@ -1,22 +0,0 @@
-//===----------------------------------------------------------------------===//
-//
-//                     The LLVM Compiler Infrastructure
-//
-// This file is dual licensed under the MIT and the University of Illinois Open
-// Source Licenses. See LICENSE.TXT for details.
-//
-//===----------------------------------------------------------------------===//
-//
-// UNSUPPORTED: newlib
-
-// <cfenv>
-
-#include <cfenv>
-
-#ifndef _LIBCPP_VERSION
-#error _LIBCPP_VERSION not defined
-#endif
-
-int main()
-{
-}
diff --git a/test/std/numerics/complex.number/cases.h b/test/std/numerics/complex.number/cases.h
index cd6bd165a9d1..a2f85d11ca4d 100644
--- a/test/std/numerics/complex.number/cases.h
+++ b/test/std/numerics/complex.number/cases.h
@@ -17,7 +17,7 @@
 #include <complex>
 #include <cassert>
 
-std::complex<double> x[] =
+const std::complex<double> testcases[] =
 {
     std::complex<double>( 1.e-6,  1.e-6),
     std::complex<double>(-1.e-6,  1.e-6),
diff --git a/test/std/numerics/complex.number/cmplx.over/imag.pass.cpp b/test/std/numerics/complex.number/cmplx.over/imag.pass.cpp
index 30c95c3c88d9..7decea877fbd 100644
--- a/test/std/numerics/complex.number/cmplx.over/imag.pass.cpp
+++ b/test/std/numerics/complex.number/cmplx.over/imag.pass.cpp
@@ -30,7 +30,7 @@ test(typename std::enable_if<std::is_integral<T>::value>::type* = 0)
     static_assert(std::imag(val) == 0, "");
     constexpr std::complex<T> t{val, val};
     static_assert(t.imag() == x, "" );
-#endif    
+#endif
 }
 
 template <class T, int x>
@@ -44,7 +44,7 @@ test(typename std::enable_if<!std::is_integral<T>::value>::type* = 0)
     static_assert(std::imag(val) == 0, "");
     constexpr std::complex<T> t{val, val};
     static_assert(t.imag() == x, "" );
-#endif    
+#endif
 }
 
 template <class T>
diff --git a/test/std/numerics/complex.number/cmplx.over/real.pass.cpp b/test/std/numerics/complex.number/cmplx.over/real.pass.cpp
index a5a4a35b13ca..491b35890c0c 100644
--- a/test/std/numerics/complex.number/cmplx.over/real.pass.cpp
+++ b/test/std/numerics/complex.number/cmplx.over/real.pass.cpp
@@ -30,7 +30,7 @@ test(typename std::enable_if<std::is_integral<T>::value>::type* = 0)
     static_assert(std::real(val) == val, "");
     constexpr std::complex<T> t{val, val};
     static_assert(t.real() == x, "" );
-#endif    
+#endif
 }
 
 template <class T, int x>
@@ -44,7 +44,7 @@ test(typename std::enable_if<!std::is_integral<T>::value>::type* = 0)
     static_assert(std::real(val) == val, "");
     constexpr std::complex<T> t{val, val};
     static_assert(t.real() == x, "" );
-#endif    
+#endif
 }
 
 template <class T>
diff --git a/test/std/numerics/complex.number/complex.literals/literals.pass.cpp b/test/std/numerics/complex.number/complex.literals/literals.pass.cpp
index 45b59914e7f8..a2e53629f97d 100644
--- a/test/std/numerics/complex.number/complex.literals/literals.pass.cpp
+++ b/test/std/numerics/complex.number/complex.literals/literals.pass.cpp
@@ -7,6 +7,7 @@
 //
 //===----------------------------------------------------------------------===//
 
+// UNSUPPORTED: c++98, c++03, c++11
 // <chrono>
 
 #include <complex>
@@ -15,7 +16,6 @@
 
 int main()
 {
-#if _LIBCPP_STD_VER > 11 
     using namespace std::literals::complex_literals;
 
 //  Make sure the types are right
@@ -25,14 +25,14 @@ int main()
     static_assert ( std::is_same<decltype( 3i    ), std::complex<double>>::value, "" );
     static_assert ( std::is_same<decltype( 3.0if ), std::complex<float>>::value, "" );
     static_assert ( std::is_same<decltype( 3if   ), std::complex<float>>::value, "" );
-    
+
     {
     std::complex<long double> c1 = 3.0il;
     assert ( c1 == std::complex<long double>(0, 3.0));
     auto c2 = 3il;
     assert ( c1 == c2 );
     }
-    
+
     {
     std::complex<double> c1 = 3.0i;
     assert ( c1 == std::complex<double>(0, 3.0));
@@ -46,6 +46,4 @@ int main()
     auto c2 = 3if;
     assert ( c1 == c2 );
     }
-
-#endif
 }
diff --git a/test/std/numerics/complex.number/complex.literals/literals1.fail.cpp b/test/std/numerics/complex.number/complex.literals/literals1.fail.cpp
index 0f31d595566c..67e0fa131fd0 100644
--- a/test/std/numerics/complex.number/complex.literals/literals1.fail.cpp
+++ b/test/std/numerics/complex.number/complex.literals/literals1.fail.cpp
@@ -7,14 +7,12 @@
 // Source Licenses. See LICENSE.TXT for details.
 //
 //===----------------------------------------------------------------------===//
+
+// UNSUPPORTED: c++98, c++03, c++11
 #include <complex>
 #include <cassert>
 
 int main()
 {
-#if _LIBCPP_STD_VER > 11 
     std::complex<float> foo  = 1.0if;  // should fail w/conversion operator not found
-#else
-#error
-#endif
 }
diff --git a/test/std/numerics/complex.number/complex.literals/literals1.pass.cpp b/test/std/numerics/complex.number/complex.literals/literals1.pass.cpp
index 46903bbd565d..09a6f270f759 100644
--- a/test/std/numerics/complex.number/complex.literals/literals1.pass.cpp
+++ b/test/std/numerics/complex.number/complex.literals/literals1.pass.cpp
@@ -7,6 +7,7 @@
 //
 //===----------------------------------------------------------------------===//
 
+// UNSUPPORTED: c++98, c++03, c++11
 // <chrono>
 
 #include <complex>
@@ -15,7 +16,6 @@
 
 int main()
 {
-#if _LIBCPP_STD_VER > 11 
     using namespace std::literals;
 
     {
@@ -24,7 +24,7 @@ int main()
     auto c2 = 3il;
     assert ( c1 == c2 );
     }
-    
+
     {
     std::complex<double> c1 = 3.0i;
     assert ( c1 == std::complex<double>(0, 3.0));
@@ -38,6 +38,4 @@ int main()
     auto c2 = 3if;
     assert ( c1 == c2 );
     }
-
-#endif
 }
diff --git a/test/std/numerics/complex.number/complex.literals/literals2.pass.cpp b/test/std/numerics/complex.number/complex.literals/literals2.pass.cpp
index 8bd8acd981bc..d11530d7803a 100644
--- a/test/std/numerics/complex.number/complex.literals/literals2.pass.cpp
+++ b/test/std/numerics/complex.number/complex.literals/literals2.pass.cpp
@@ -7,6 +7,7 @@
 //
 //===----------------------------------------------------------------------===//
 
+// UNSUPPORTED: c++98, c++03, c++11
 // <chrono>
 
 #include <complex>
@@ -15,7 +16,6 @@
 
 int main()
 {
-#if _LIBCPP_STD_VER > 11 
     using namespace std;
 
     {
@@ -24,7 +24,7 @@ int main()
     auto c2 = 3il;
     assert ( c1 == c2 );
     }
-    
+
     {
     std::complex<double> c1 = 3.0i;
     assert ( c1 == std::complex<double>(0, 3.0));
@@ -38,6 +38,4 @@ int main()
     auto c2 = 3if;
     assert ( c1 == c2 );
     }
-
-#endif
 }
diff --git a/test/std/numerics/complex.number/complex.member.ops/divide_equal_complex.pass.cpp b/test/std/numerics/complex.number/complex.member.ops/divide_equal_complex.pass.cpp
index cb285117b15d..b4200fc81d40 100644
--- a/test/std/numerics/complex.number/complex.member.ops/divide_equal_complex.pass.cpp
+++ b/test/std/numerics/complex.number/complex.member.ops/divide_equal_complex.pass.cpp
@@ -28,7 +28,7 @@ test()
     c /= c2;
     assert(c.real() == 1);
     assert(c.imag() == 0);
-    
+
     std::complex<T> c3;
 
     c3 = c;
@@ -36,13 +36,13 @@ test()
     c3 /= ic;
     assert(c3.real() ==  0.5);
     assert(c3.imag() == -0.5);
-    
+
     c3 = c;
     std::complex<float> fc (1,1);
     c3 /= fc;
     assert(c3.real() ==  0.5);
     assert(c3.imag() == -0.5);
-    
+
 }
 
 int main()
diff --git a/test/std/numerics/complex.number/complex.member.ops/plus_equal_complex.pass.cpp b/test/std/numerics/complex.number/complex.member.ops/plus_equal_complex.pass.cpp
index 8c16f4ced2cd..9b222b8a1d3c 100644
--- a/test/std/numerics/complex.number/complex.member.ops/plus_equal_complex.pass.cpp
+++ b/test/std/numerics/complex.number/complex.member.ops/plus_equal_complex.pass.cpp
@@ -36,7 +36,7 @@ test()
     c3 += ic;
     assert(c3.real() == 4);
     assert(c3.imag() == 6);
-    
+
     c3 = c;
     std::complex<float> fc (1,1);
     c3 += fc;
diff --git a/test/std/numerics/complex.number/complex.member.ops/times_equal_complex.pass.cpp b/test/std/numerics/complex.number/complex.member.ops/times_equal_complex.pass.cpp
index 84d6e591306e..98b7197cb272 100644
--- a/test/std/numerics/complex.number/complex.member.ops/times_equal_complex.pass.cpp
+++ b/test/std/numerics/complex.number/complex.member.ops/times_equal_complex.pass.cpp
@@ -36,7 +36,7 @@ test()
     c3 *= ic;
     assert(c3.real() == -11.5);
     assert(c3.imag() ==   3.5);
-    
+
     c3 = c;
     std::complex<float> fc (1,1);
     c3 *= fc;
diff --git a/test/std/numerics/complex.number/complex.ops/complex_divide_complex.pass.cpp b/test/std/numerics/complex.number/complex.ops/complex_divide_complex.pass.cpp
index 86119678aa70..8d4712eece78 100644
--- a/test/std/numerics/complex.number/complex.ops/complex_divide_complex.pass.cpp
+++ b/test/std/numerics/complex.number/complex.ops/complex_divide_complex.pass.cpp
@@ -37,16 +37,16 @@ test()
 
 void test_edges()
 {
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
         for (unsigned j = 0; j < N; ++j)
         {
-            std::complex<double> r = x[i] / x[j];
-            switch (classify(x[i]))
+            std::complex<double> r = testcases[i] / testcases[j];
+            switch (classify(testcases[i]))
             {
             case zero:
-                switch (classify(x[j]))
+                switch (classify(testcases[j]))
                 {
                 case zero:
                     assert(classify(r) == NaN);
@@ -66,7 +66,7 @@ void test_edges()
                 }
                 break;
             case non_zero:
-                switch (classify(x[j]))
+                switch (classify(testcases[j]))
                 {
                 case zero:
                     assert(classify(r) == inf);
@@ -86,7 +86,7 @@ void test_edges()
                 }
                 break;
             case inf:
-                switch (classify(x[j]))
+                switch (classify(testcases[j]))
                 {
                 case zero:
                     assert(classify(r) == inf);
@@ -106,7 +106,7 @@ void test_edges()
                 }
                 break;
             case NaN:
-                switch (classify(x[j]))
+                switch (classify(testcases[j]))
                 {
                 case zero:
                     assert(classify(r) == NaN);
@@ -126,7 +126,7 @@ void test_edges()
                 }
                 break;
             case non_zero_nan:
-                switch (classify(x[j]))
+                switch (classify(testcases[j]))
                 {
                 case zero:
                     assert(classify(r) == inf);
diff --git a/test/std/numerics/complex.number/complex.ops/complex_times_complex.pass.cpp b/test/std/numerics/complex.number/complex.ops/complex_times_complex.pass.cpp
index 565eaa5657cd..8ead5bfb627a 100644
--- a/test/std/numerics/complex.number/complex.ops/complex_times_complex.pass.cpp
+++ b/test/std/numerics/complex.number/complex.ops/complex_times_complex.pass.cpp
@@ -39,16 +39,16 @@ test()
 
 void test_edges()
 {
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
         for (unsigned j = 0; j < N; ++j)
         {
-            std::complex<double> r = x[i] * x[j];
-            switch (classify(x[i]))
+            std::complex<double> r = testcases[i] * testcases[j];
+            switch (classify(testcases[i]))
             {
             case zero:
-                switch (classify(x[j]))
+                switch (classify(testcases[j]))
                 {
                 case zero:
                     assert(classify(r) == zero);
@@ -68,7 +68,7 @@ void test_edges()
                 }
                 break;
             case non_zero:
-                switch (classify(x[j]))
+                switch (classify(testcases[j]))
                 {
                 case zero:
                     assert(classify(r) == zero);
@@ -88,7 +88,7 @@ void test_edges()
                 }
                 break;
             case inf:
-                switch (classify(x[j]))
+                switch (classify(testcases[j]))
                 {
                 case zero:
                     assert(classify(r) == NaN);
@@ -108,7 +108,7 @@ void test_edges()
                 }
                 break;
             case NaN:
-                switch (classify(x[j]))
+                switch (classify(testcases[j]))
                 {
                 case zero:
                     assert(classify(r) == NaN);
@@ -128,7 +128,7 @@ void test_edges()
                 }
                 break;
             case non_zero_nan:
-                switch (classify(x[j]))
+                switch (classify(testcases[j]))
                 {
                 case zero:
                     assert(classify(r) == NaN);
diff --git a/test/std/numerics/complex.number/complex.transcendentals/acos.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/acos.pass.cpp
index f8ee306d7544..1b0cca0d5f69 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/acos.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/acos.pass.cpp
@@ -36,94 +36,94 @@ void test_edges()
 {
     typedef std::complex<double> C;
     const double pi = std::atan2(+0., -0.);
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        std::complex<double> r = acos(x[i]);
-        if (x[i].real() == 0 && x[i].imag() == 0)
+        std::complex<double> r = acos(testcases[i]);
+        if (testcases[i].real() == 0 && testcases[i].imag() == 0)
         {
             is_about(r.real(), pi/2);
             assert(r.imag() == 0);
-            assert(std::signbit(x[i].imag()) != std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) != std::signbit(r.imag()));
         }
-        else if (x[i].real() == 0 && std::isnan(x[i].imag()))
+        else if (testcases[i].real() == 0 && std::isnan(testcases[i].imag()))
         {
             is_about(r.real(), pi/2);
             assert(std::isnan(r.imag()));
         }
-        else if (std::isfinite(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             is_about(r.real(), pi/2);
             assert(std::isinf(r.imag()));
-            assert(std::signbit(x[i].imag()) != std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) != std::signbit(r.imag()));
         }
-        else if (std::isfinite(x[i].real()) && x[i].real() != 0 && std::isnan(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && testcases[i].real() != 0 && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && x[i].real() < 0 && std::isfinite(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() < 0 && std::isfinite(testcases[i].imag()))
         {
             is_about(r.real(), pi);
             assert(std::isinf(r.imag()));
-            assert(std::signbit(x[i].imag()) != std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) != std::signbit(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && x[i].real() > 0 && std::isfinite(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() > 0 && std::isfinite(testcases[i].imag()))
         {
             assert(r.real() == 0);
             assert(!std::signbit(r.real()));
             assert(std::isinf(r.imag()));
-            assert(std::signbit(x[i].imag()) != std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) != std::signbit(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && x[i].real() < 0 && std::isinf(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() < 0 && std::isinf(testcases[i].imag()))
         {
             is_about(r.real(), 0.75 * pi);
             assert(std::isinf(r.imag()));
-            assert(std::signbit(x[i].imag()) != std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) != std::signbit(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && x[i].real() > 0 && std::isinf(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() > 0 && std::isinf(testcases[i].imag()))
         {
             is_about(r.real(), 0.25 * pi);
             assert(std::isinf(r.imag()));
-            assert(std::signbit(x[i].imag()) != std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) != std::signbit(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isinf(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isfinite(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isfinite(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isinf(r.imag()));
-            assert(std::signbit(x[i].imag()) != std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) != std::signbit(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (!std::signbit(x[i].real()) && !std::signbit(x[i].imag()))
+        else if (!std::signbit(testcases[i].real()) && !std::signbit(testcases[i].imag()))
         {
             assert(!std::signbit(r.real()));
             assert( std::signbit(r.imag()));
         }
-        else if (std::signbit(x[i].real()) && !std::signbit(x[i].imag()))
+        else if (std::signbit(testcases[i].real()) && !std::signbit(testcases[i].imag()))
         {
             assert(!std::signbit(r.real()));
             assert( std::signbit(r.imag()));
         }
-        else if (std::signbit(x[i].real()) && std::signbit(x[i].imag()))
+        else if (std::signbit(testcases[i].real()) && std::signbit(testcases[i].imag()))
         {
             assert(!std::signbit(r.real()));
             assert(!std::signbit(r.imag()));
         }
-        else if (!std::signbit(x[i].real()) && std::signbit(x[i].imag()))
+        else if (!std::signbit(testcases[i].real()) && std::signbit(testcases[i].imag()))
         {
             assert(!std::signbit(r.real()));
             assert(!std::signbit(r.imag()));
diff --git a/test/std/numerics/complex.number/complex.transcendentals/acosh.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/acosh.pass.cpp
index 88a5c798424d..f1aece20e6cf 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/acosh.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/acosh.pass.cpp
@@ -36,91 +36,91 @@ void test_edges()
 {
     typedef std::complex<double> C;
     const double pi = std::atan2(+0., -0.);
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        std::complex<double> r = acosh(x[i]);
-        if (x[i].real() == 0 && x[i].imag() == 0)
+        std::complex<double> r = acosh(testcases[i]);
+        if (testcases[i].real() == 0 && testcases[i].imag() == 0)
         {
             assert(!std::signbit(r.real()));
-            if (std::signbit(x[i].imag()))
+            if (std::signbit(testcases[i].imag()))
                 is_about(r.imag(), -pi/2);
             else
                 is_about(r.imag(),  pi/2);
         }
-        else if (x[i].real() == 1 && x[i].imag() == 0)
+        else if (testcases[i].real() == 1 && testcases[i].imag() == 0)
         {
             assert(r.real() == 0);
             assert(!std::signbit(r.real()));
             assert(r.imag() == 0);
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
-        else if (std::isfinite(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(r.real() > 0);
-            if (std::signbit(x[i].imag()))
+            if (std::signbit(testcases[i].imag()))
                 is_about(r.imag(), -pi/2);
             else
                 is_about(r.imag(),  pi/2);
         }
-        else if (std::isfinite(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && x[i].real() < 0 && std::isfinite(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() < 0 && std::isfinite(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(r.real() > 0);
-            if (std::signbit(x[i].imag()))
+            if (std::signbit(testcases[i].imag()))
                 is_about(r.imag(), -pi);
             else
                 is_about(r.imag(),  pi);
         }
-        else if (std::isinf(x[i].real()) && x[i].real() > 0 && std::isfinite(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() > 0 && std::isfinite(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(r.real() > 0);
             assert(r.imag() == 0);
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
-        else if (std::isinf(x[i].real()) && x[i].real() < 0 && std::isinf(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() < 0 && std::isinf(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(r.real() > 0);
-            if (std::signbit(x[i].imag()))
+            if (std::signbit(testcases[i].imag()))
                 is_about(r.imag(), -0.75 * pi);
             else
                 is_about(r.imag(),  0.75 * pi);
         }
-        else if (std::isinf(x[i].real()) && x[i].real() > 0 && std::isinf(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() > 0 && std::isinf(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(r.real() > 0);
-            if (std::signbit(x[i].imag()))
+            if (std::signbit(testcases[i].imag()))
                 is_about(r.imag(), -0.25 * pi);
             else
                 is_about(r.imag(),  0.25 * pi);
         }
-        else if (std::isinf(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(r.real() > 0);
             assert(std::isnan(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isfinite(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isfinite(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(r.real() > 0);
             assert(std::isnan(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
@@ -128,7 +128,7 @@ void test_edges()
         else
         {
             assert(!std::signbit(r.real()));
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
     }
 }
diff --git a/test/std/numerics/complex.number/complex.transcendentals/asin.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/asin.pass.cpp
index c743be6488c6..cf6f7869bd1a 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/asin.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/asin.pass.cpp
@@ -36,77 +36,77 @@ void test_edges()
 {
     typedef std::complex<double> C;
     const double pi = std::atan2(+0., -0.);
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        std::complex<double> r = asin(x[i]);
-        if (x[i].real() == 0 && x[i].imag() == 0)
+        std::complex<double> r = asin(testcases[i]);
+        if (testcases[i].real() == 0 && testcases[i].imag() == 0)
         {
-            assert(std::signbit(r.real()) == std::signbit(x[i].real()));
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.real()) == std::signbit(testcases[i].real()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
-        else if (std::isfinite(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(r.real() == 0);
-            assert(std::signbit(x[i].real()) == std::signbit(r.real()));
+            assert(std::signbit(testcases[i].real()) == std::signbit(r.real()));
             assert(std::isinf(r.imag()));
-            assert(std::signbit(x[i].imag()) == std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) == std::signbit(r.imag()));
         }
-        else if ( x[i].real() == 0 && std::isnan(x[i].imag()))
+        else if ( testcases[i].real() == 0 && std::isnan(testcases[i].imag()))
         {
             assert(r.real() == 0);
-            assert(std::signbit(x[i].real()) == std::signbit(r.real()));
+            assert(std::signbit(testcases[i].real()) == std::signbit(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isfinite(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && std::isfinite(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isfinite(testcases[i].imag()))
         {
-            if (x[i].real() > 0)
+            if (testcases[i].real() > 0)
                 is_about(r.real(),  pi/2);
             else
                 is_about(r.real(), - pi/2);
             assert(std::isinf(r.imag()));
-            assert(std::signbit(x[i].imag()) == std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) == std::signbit(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
-            if (std::signbit(x[i].real()))
+            if (std::signbit(testcases[i].real()))
                 is_about(r.real(), -pi/4);
             else
                 is_about(r.real(),  pi/4);
             assert(std::isinf(r.imag()));
-            assert(std::signbit(x[i].imag()) == std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) == std::signbit(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isinf(r.imag()));
-            assert(std::signbit(x[i].real()) != std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].real()) != std::signbit(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isfinite(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isfinite(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
-            assert(std::signbit(x[i].imag()) == std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) == std::signbit(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isinf(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
         else
         {
-            assert(std::signbit(r.real()) == std::signbit(x[i].real()));
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.real()) == std::signbit(testcases[i].real()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
     }
 }
diff --git a/test/std/numerics/complex.number/complex.transcendentals/asinh.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/asinh.pass.cpp
index 027bc6a98a99..011f9d6b4f2e 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/asinh.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/asinh.pass.cpp
@@ -36,76 +36,76 @@ void test_edges()
 {
     typedef std::complex<double> C;
     const double pi = std::atan2(+0., -0.);
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        std::complex<double> r = asinh(x[i]);
-        if (x[i].real() == 0 && x[i].imag() == 0)
+        std::complex<double> r = asinh(testcases[i]);
+        if (testcases[i].real() == 0 && testcases[i].imag() == 0)
         {
-            assert(std::signbit(r.real()) == std::signbit(x[i].real()));
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.real()) == std::signbit(testcases[i].real()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
-        else if (std::isfinite(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
-            assert(std::signbit(x[i].real()) == std::signbit(r.real()));
-            if (std::signbit(x[i].imag()))
+            assert(std::signbit(testcases[i].real()) == std::signbit(r.real()));
+            if (std::signbit(testcases[i].imag()))
                 is_about(r.imag(), -pi/2);
             else
                 is_about(r.imag(),  pi/2);
         }
-        else if (std::isfinite(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && std::isfinite(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isfinite(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
-            assert(std::signbit(x[i].real()) == std::signbit(r.real()));
+            assert(std::signbit(testcases[i].real()) == std::signbit(r.real()));
             assert(r.imag() == 0);
-            assert(std::signbit(x[i].imag()) == std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) == std::signbit(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
-            assert(std::signbit(x[i].real()) == std::signbit(r.real()));
-            if (std::signbit(x[i].imag()))
+            assert(std::signbit(testcases[i].real()) == std::signbit(r.real()));
+            if (std::signbit(testcases[i].imag()))
                 is_about(r.imag(), -pi/4);
             else
                 is_about(r.imag(),  pi/4);
         }
-        else if (std::isinf(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
-            assert(std::signbit(x[i].real()) == std::signbit(r.real()));
+            assert(std::signbit(testcases[i].real()) == std::signbit(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && x[i].imag() == 0)
+        else if (std::isnan(testcases[i].real()) && testcases[i].imag() == 0)
         {
             assert(std::isnan(r.real()));
             assert(r.imag() == 0);
-            assert(std::signbit(x[i].imag()) == std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) == std::signbit(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isfinite(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isfinite(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
         else
         {
-            assert(std::signbit(r.real()) == std::signbit(x[i].real()));
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.real()) == std::signbit(testcases[i].real()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
     }
 }
diff --git a/test/std/numerics/complex.number/complex.transcendentals/atan.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/atan.pass.cpp
index 69bc95240141..8cc71f7bff27 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/atan.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/atan.pass.cpp
@@ -35,11 +35,11 @@ test()
 void test_edges()
 {
     typedef std::complex<double> C;
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        std::complex<double> r = atan(x[i]);
-        std::complex<double> t1(-imag(x[i]), real(x[i]));
+        std::complex<double> r = atan(testcases[i]);
+        std::complex<double> t1(-imag(testcases[i]), real(testcases[i]));
         std::complex<double> t2 = atanh(t1);
         std::complex<double> z(imag(t2), -real(t2));
         if (std::isnan(real(r)))
diff --git a/test/std/numerics/complex.number/complex.transcendentals/atanh.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/atanh.pass.cpp
index b821109b751b..6dc6034ca3c6 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/atanh.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/atanh.pass.cpp
@@ -36,89 +36,89 @@ void test_edges()
 {
     typedef std::complex<double> C;
     const double pi = std::atan2(+0., -0.);
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        std::complex<double> r = atanh(x[i]);
-        if (x[i].real() == 0 && x[i].imag() == 0)
+        std::complex<double> r = atanh(testcases[i]);
+        if (testcases[i].real() == 0 && testcases[i].imag() == 0)
         {
-            assert(std::signbit(r.real()) == std::signbit(x[i].real()));
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.real()) == std::signbit(testcases[i].real()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
-        else if ( x[i].real() == 0 && std::isnan(x[i].imag()))
+        else if ( testcases[i].real() == 0 && std::isnan(testcases[i].imag()))
         {
             assert(r.real() == 0);
-            assert(std::signbit(x[i].real()) == std::signbit(r.real()));
+            assert(std::signbit(testcases[i].real()) == std::signbit(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::abs(x[i].real()) == 1 && x[i].imag() == 0)
+        else if (std::abs(testcases[i].real()) == 1 && testcases[i].imag() == 0)
         {
             assert(std::isinf(r.real()));
-            assert(std::signbit(x[i].real()) == std::signbit(r.real()));
+            assert(std::signbit(testcases[i].real()) == std::signbit(r.real()));
             assert(r.imag() == 0);
-            assert(std::signbit(x[i].imag()) == std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) == std::signbit(r.imag()));
         }
-        else if (std::isfinite(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(r.real() == 0);
-            assert(std::signbit(x[i].real()) == std::signbit(r.real()));
-            if (x[i].imag() > 0)
+            assert(std::signbit(testcases[i].real()) == std::signbit(r.real()));
+            if (testcases[i].imag() > 0)
                 is_about(r.imag(),  pi/2);
             else
                 is_about(r.imag(), -pi/2);
         }
-        else if (std::isfinite(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && std::isfinite(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isfinite(testcases[i].imag()))
         {
             assert(r.real() == 0);
-            assert(std::signbit(x[i].real()) == std::signbit(r.real()));
-            if (std::signbit(x[i].imag()))
+            assert(std::signbit(testcases[i].real()) == std::signbit(r.real()));
+            if (std::signbit(testcases[i].imag()))
                 is_about(r.imag(), -pi/2);
             else
                 is_about(r.imag(),  pi/2);
         }
-        else if (std::isinf(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(r.real() == 0);
-            assert(std::signbit(x[i].real()) == std::signbit(r.real()));
-            if (std::signbit(x[i].imag()))
+            assert(std::signbit(testcases[i].real()) == std::signbit(r.real()));
+            if (std::signbit(testcases[i].imag()))
                 is_about(r.imag(), -pi/2);
             else
                 is_about(r.imag(),  pi/2);
         }
-        else if (std::isinf(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(r.real() == 0);
-            assert(std::signbit(x[i].real()) == std::signbit(r.real()));
+            assert(std::signbit(testcases[i].real()) == std::signbit(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isfinite(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isfinite(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(r.real() == 0);
-            assert(std::signbit(x[i].real()) == std::signbit(r.real()));
-            if (std::signbit(x[i].imag()))
+            assert(std::signbit(testcases[i].real()) == std::signbit(r.real()));
+            if (std::signbit(testcases[i].imag()))
                 is_about(r.imag(), -pi/2);
             else
                 is_about(r.imag(),  pi/2);
         }
-        else if (std::isnan(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
         else
         {
-            assert(std::signbit(r.real()) == std::signbit(x[i].real()));
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.real()) == std::signbit(testcases[i].real()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
     }
 }
diff --git a/test/std/numerics/complex.number/complex.transcendentals/cos.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/cos.pass.cpp
index f25c967cb1a7..e09163a7057d 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/cos.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/cos.pass.cpp
@@ -36,11 +36,11 @@ void test_edges()
 {
     typedef std::complex<double> C;
     const double pi = std::atan2(+0., -0.);
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        std::complex<double> r = cos(x[i]);
-        std::complex<double> t1(-imag(x[i]), real(x[i]));
+        std::complex<double> r = cos(testcases[i]);
+        std::complex<double> t1(-imag(testcases[i]), real(testcases[i]));
         std::complex<double> z = cosh(t1);
         if (std::isnan(real(r)))
             assert(std::isnan(real(z)));
diff --git a/test/std/numerics/complex.number/complex.transcendentals/cosh.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/cosh.pass.cpp
index acf4746389c8..0fd9cf79bcbf 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/cosh.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/cosh.pass.cpp
@@ -36,72 +36,72 @@ void test_edges()
 {
     typedef std::complex<double> C;
     const double pi = std::atan2(+0., -0.);
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        std::complex<double> r = cosh(x[i]);
-        if (x[i].real() == 0 && x[i].imag() == 0)
+        std::complex<double> r = cosh(testcases[i]);
+        if (testcases[i].real() == 0 && testcases[i].imag() == 0)
         {
             assert(r.real() == 1);
             assert(r.imag() == 0);
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
-        else if (x[i].real() == 0 && std::isinf(x[i].imag()))
+        else if (testcases[i].real() == 0 && std::isinf(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(r.imag() == 0);
         }
-        else if (x[i].real() == 0 && std::isnan(x[i].imag()))
+        else if (testcases[i].real() == 0 && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(r.imag() == 0);
         }
-        else if (std::isfinite(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isfinite(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && x[i].imag() == 0)
+        else if (std::isinf(testcases[i].real()) && testcases[i].imag() == 0)
         {
             assert(std::isinf(r.real()));
             assert(!std::signbit(r.real()));
             assert(r.imag() == 0);
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
-        else if (std::isinf(x[i].real()) && std::isfinite(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isfinite(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
-            assert(std::signbit(r.real()) == std::signbit(cos(x[i].imag())));
+            assert(std::signbit(r.real()) == std::signbit(cos(testcases[i].imag())));
             assert(std::isinf(r.imag()));
-            assert(std::signbit(r.imag()) == std::signbit(x[i].real() * sin(x[i].imag())));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].real() * sin(testcases[i].imag())));
         }
-        else if (std::isinf(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(r.real() > 0);
             assert(std::isnan(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && x[i].imag() == 0)
+        else if (std::isnan(testcases[i].real()) && testcases[i].imag() == 0)
         {
             assert(std::isnan(r.real()));
             assert(r.imag() == 0);
         }
-        else if (std::isnan(x[i].real()) && std::isfinite(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isfinite(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
diff --git a/test/std/numerics/complex.number/complex.transcendentals/exp.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/exp.pass.cpp
index e8b507572f1b..31317816fae0 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/exp.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/exp.pass.cpp
@@ -34,73 +34,73 @@ test()
 
 void test_edges()
 {
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        std::complex<double> r = exp(x[i]);
-        if (x[i].real() == 0 && x[i].imag() == 0)
+        std::complex<double> r = exp(testcases[i]);
+        if (testcases[i].real() == 0 && testcases[i].imag() == 0)
         {
             assert(r.real() == 1.0);
             assert(r.imag() == 0);
-            assert(std::signbit(x[i].imag()) == std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) == std::signbit(r.imag()));
         }
-        else if (std::isfinite(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isfinite(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && x[i].real() > 0 && x[i].imag() == 0)
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() > 0 && testcases[i].imag() == 0)
         {
             assert(std::isinf(r.real()));
             assert(r.real() > 0);
             assert(r.imag() == 0);
-            assert(std::signbit(x[i].imag()) == std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) == std::signbit(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && x[i].real() < 0 && std::isinf(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() < 0 && std::isinf(testcases[i].imag()))
         {
             assert(r.real() == 0);
             assert(r.imag() == 0);
         }
-        else if (std::isinf(x[i].real()) && x[i].real() > 0 && std::isinf(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() > 0 && std::isinf(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && x[i].real() < 0 && std::isnan(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() < 0 && std::isnan(testcases[i].imag()))
         {
             assert(r.real() == 0);
             assert(r.imag() == 0);
         }
-        else if (std::isinf(x[i].real()) && x[i].real() > 0 && std::isnan(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() > 0 && std::isnan(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && x[i].imag() == 0)
+        else if (std::isnan(testcases[i].real()) && testcases[i].imag() == 0)
         {
             assert(std::isnan(r.real()));
             assert(r.imag() == 0);
-            assert(std::signbit(x[i].imag()) == std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) == std::signbit(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && x[i].imag() != 0)
+        else if (std::isnan(testcases[i].real()) && testcases[i].imag() != 0)
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isfinite(x[i].imag()) && std::abs(x[i].imag()) <= 1)
+        else if (std::isfinite(testcases[i].imag()) && std::abs(testcases[i].imag()) <= 1)
         {
             assert(!std::signbit(r.real()));
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
     }
 }
diff --git a/test/std/numerics/complex.number/complex.transcendentals/log.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/log.pass.cpp
index 800b92474bf0..589b5969950d 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/log.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/log.pass.cpp
@@ -35,17 +35,17 @@ test()
 void test_edges()
 {
     const double pi = std::atan2(+0., -0.);
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        std::complex<double> r = log(x[i]);
-        if (x[i].real() == 0 && x[i].imag() == 0)
+        std::complex<double> r = log(testcases[i]);
+        if (testcases[i].real() == 0 && testcases[i].imag() == 0)
         {
-            if (std::signbit(x[i].real()))
+            if (std::signbit(testcases[i].real()))
             {
                 assert(std::isinf(r.real()));
                 assert(r.real() < 0);
-                if (std::signbit(x[i].imag()))
+                if (std::signbit(testcases[i].imag()))
                     is_about(r.imag(), -pi);
                 else
                     is_about(r.imag(), pi);
@@ -55,24 +55,24 @@ void test_edges()
                 assert(std::isinf(r.real()));
                 assert(r.real() < 0);
                 assert(r.imag() == 0);
-                assert(std::signbit(x[i].imag()) == std::signbit(r.imag()));
+                assert(std::signbit(testcases[i].imag()) == std::signbit(r.imag()));
             }
         }
-        else if (std::isfinite(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(r.real() > 0);
-            if (x[i].imag() > 0)
+            if (testcases[i].imag() > 0)
                 is_about(r.imag(), pi/2);
             else
                 is_about(r.imag(), -pi/2);
         }
-        else if (std::isfinite(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && x[i].real() < 0 && std::isfinite(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() < 0 && std::isfinite(testcases[i].imag()))
         {
             assert(std::isinf(r.real()) && r.real() > 0);
             if (r.imag() > 0)
@@ -80,44 +80,44 @@ void test_edges()
             else
                 is_about(r.imag(), -pi);
         }
-        else if (std::isinf(x[i].real()) && x[i].real() > 0 && std::isfinite(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() > 0 && std::isfinite(testcases[i].imag()))
         {
             assert(std::isinf(r.real()) && r.real() > 0);
             assert(r.imag() == 0);
-            assert(std::signbit(x[i].imag()) == std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) == std::signbit(r.imag()));
         }
-        else if (x[i].real() == 1 && x[i].imag() == 0)
+        else if (testcases[i].real() == 1 && testcases[i].imag() == 0)
         {
             assert(r.real() == 0);
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
-        else if (x[i].real() == 0 && x[i].imag() == 1)
+        else if (testcases[i].real() == 0 && testcases[i].imag() == 1)
         {
             assert(r.real() == 0);
             is_about(r.imag(), pi/2);
         }
-        else if (x[i].real() == -1 && x[i].imag() == 0)
+        else if (testcases[i].real() == -1 && testcases[i].imag() == 0)
         {
             assert(r.real() == 0);
-            if (std::signbit(x[i].imag()))
+            if (std::signbit(testcases[i].imag()))
                 is_about(r.imag(), -pi);
             else
                 is_about(r.imag(),  pi);
         }
-        else if (x[i].real() == 0 && x[i].imag() == -1)
+        else if (testcases[i].real() == 0 && testcases[i].imag() == -1)
         {
             assert(r.real() == 0);
             is_about(r.imag(), -pi/2);
         }
-        else if (std::isfinite(x[i].real()) && std::isfinite(x[i].imag()) && abs(x[i]) < 1)
+        else if (std::isfinite(testcases[i].real()) && std::isfinite(testcases[i].imag()) && abs(testcases[i]) < 1)
         {
             assert( std::signbit(r.real()));
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
-        else if (std::isfinite(x[i].real()) && std::isfinite(x[i].imag()) && abs(x[i]) > 1)
+        else if (std::isfinite(testcases[i].real()) && std::isfinite(testcases[i].imag()) && abs(testcases[i]) > 1)
         {
             assert(!std::signbit(r.real()));
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
     }
 }
diff --git a/test/std/numerics/complex.number/complex.transcendentals/log10.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/log10.pass.cpp
index ba03ebf8ad28..58286904ae25 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/log10.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/log10.pass.cpp
@@ -35,11 +35,11 @@ test()
 void test_edges()
 {
     const double pi = std::atan2(+0., -0.);
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        std::complex<double> r = log10(x[i]);
-        std::complex<double> z = log(x[i])/std::log(10);
+        std::complex<double> r = log10(testcases[i]);
+        std::complex<double> z = log(testcases[i])/std::log(10);
         if (std::isnan(real(r)))
             assert(std::isnan(real(z)));
         else
diff --git a/test/std/numerics/complex.number/complex.transcendentals/pow_complex_complex.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/pow_complex_complex.pass.cpp
index 258193d257a8..157246947cfe 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/pow_complex_complex.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/pow_complex_complex.pass.cpp
@@ -37,13 +37,13 @@ test()
 void test_edges()
 {
     const double pi = std::atan2(+0., -0.);
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
         for (unsigned j = 0; j < N; ++j)
         {
-            std::complex<double> r = pow(x[i], x[j]);
-            std::complex<double> z = exp(x[j] * log(x[i]));
+            std::complex<double> r = pow(testcases[i], testcases[j]);
+            std::complex<double> z = exp(testcases[j] * log(testcases[i]));
             if (std::isnan(real(r)))
                 assert(std::isnan(real(z)));
             else
diff --git a/test/std/numerics/complex.number/complex.transcendentals/pow_complex_scalar.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/pow_complex_scalar.pass.cpp
index 03bd10d465d1..0752ea59f554 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/pow_complex_scalar.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/pow_complex_scalar.pass.cpp
@@ -37,13 +37,13 @@ test()
 void test_edges()
 {
     const double pi = std::atan2(+0., -0.);
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
         for (unsigned j = 0; j < N; ++j)
         {
-            std::complex<double> r = pow(x[i], real(x[j]));
-            std::complex<double> z = exp(std::complex<double>(real(x[j])) * log(x[i]));
+            std::complex<double> r = pow(testcases[i], real(testcases[j]));
+            std::complex<double> z = exp(std::complex<double>(real(testcases[j])) * log(testcases[i]));
             if (std::isnan(real(r)))
                 assert(std::isnan(real(z)));
             else
diff --git a/test/std/numerics/complex.number/complex.transcendentals/pow_scalar_complex.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/pow_scalar_complex.pass.cpp
index a48498cea92c..aedeec8caacc 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/pow_scalar_complex.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/pow_scalar_complex.pass.cpp
@@ -37,13 +37,13 @@ test()
 void test_edges()
 {
     const double pi = std::atan2(+0., -0.);
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
         for (unsigned j = 0; j < N; ++j)
         {
-            std::complex<double> r = pow(real(x[i]), x[j]);
-            std::complex<double> z = exp(x[j] * log(std::complex<double>(real(x[i]))));
+            std::complex<double> r = pow(real(testcases[i]), testcases[j]);
+            std::complex<double> z = exp(testcases[j] * log(std::complex<double>(real(testcases[i]))));
             if (std::isnan(real(r)))
                 assert(std::isnan(real(z)));
             else
diff --git a/test/std/numerics/complex.number/complex.transcendentals/sin.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/sin.pass.cpp
index 068222a27373..e1b98ecd0677 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/sin.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/sin.pass.cpp
@@ -36,11 +36,11 @@ void test_edges()
 {
     typedef std::complex<double> C;
     const double pi = std::atan2(+0., -0.);
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        std::complex<double> r = sin(x[i]);
-        std::complex<double> t1(-imag(x[i]), real(x[i]));
+        std::complex<double> r = sin(testcases[i]);
+        std::complex<double> t1(-imag(testcases[i]), real(testcases[i]));
         std::complex<double> t2 = sinh(t1);
         std::complex<double> z(imag(t2), -real(t2));
         if (std::isnan(real(r)))
diff --git a/test/std/numerics/complex.number/complex.transcendentals/sinh.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/sinh.pass.cpp
index dcd30e48dff5..20f2e71b140a 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/sinh.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/sinh.pass.cpp
@@ -36,73 +36,73 @@ void test_edges()
 {
     typedef std::complex<double> C;
     const double pi = std::atan2(+0., -0.);
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        std::complex<double> r = sinh(x[i]);
-        if (x[i].real() == 0 && x[i].imag() == 0)
+        std::complex<double> r = sinh(testcases[i]);
+        if (testcases[i].real() == 0 && testcases[i].imag() == 0)
         {
             assert(r.real() == 0);
-            assert(std::signbit(r.real()) == std::signbit(x[i].real()));
+            assert(std::signbit(r.real()) == std::signbit(testcases[i].real()));
             assert(r.imag() == 0);
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
-        else if (x[i].real() == 0 && std::isinf(x[i].imag()))
+        else if (testcases[i].real() == 0 && std::isinf(testcases[i].imag()))
         {
             assert(r.real() == 0);
             assert(std::isnan(r.imag()));
         }
-        else if (std::isfinite(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (x[i].real() == 0 && std::isnan(x[i].imag()))
+        else if (testcases[i].real() == 0 && std::isnan(testcases[i].imag()))
         {
             assert(r.real() == 0);
             assert(std::isnan(r.imag()));
         }
-        else if (std::isfinite(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && x[i].imag() == 0)
+        else if (std::isinf(testcases[i].real()) && testcases[i].imag() == 0)
         {
             assert(std::isinf(r.real()));
-            assert(std::signbit(r.real()) == std::signbit(x[i].real()));
+            assert(std::signbit(r.real()) == std::signbit(testcases[i].real()));
             assert(r.imag() == 0);
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
-        else if (std::isinf(x[i].real()) && std::isfinite(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isfinite(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
-            assert(std::signbit(r.real()) == std::signbit(x[i].real() * cos(x[i].imag())));
+            assert(std::signbit(r.real()) == std::signbit(testcases[i].real() * cos(testcases[i].imag())));
             assert(std::isinf(r.imag()));
-            assert(std::signbit(r.imag()) == std::signbit(sin(x[i].imag())));
+            assert(std::signbit(r.imag()) == std::signbit(sin(testcases[i].imag())));
         }
-        else if (std::isinf(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && x[i].imag() == 0)
+        else if (std::isnan(testcases[i].real()) && testcases[i].imag() == 0)
         {
             assert(std::isnan(r.real()));
             assert(r.imag() == 0);
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isfinite(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isfinite(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
diff --git a/test/std/numerics/complex.number/complex.transcendentals/sqrt.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/sqrt.pass.cpp
index 69309d2b9ab1..d3273179a6da 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/sqrt.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/sqrt.pass.cpp
@@ -36,58 +36,58 @@ test()
 
 void test_edges()
 {
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        std::complex<double> r = sqrt(x[i]);
-        if (x[i].real() == 0 && x[i].imag() == 0)
+        std::complex<double> r = sqrt(testcases[i]);
+        if (testcases[i].real() == 0 && testcases[i].imag() == 0)
         {
             assert(!std::signbit(r.real()));
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
-        else if (std::isinf(x[i].imag()))
+        else if (std::isinf(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(r.real() > 0);
             assert(std::isinf(r.imag()));
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
-        else if (std::isfinite(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && x[i].real() < 0 && std::isfinite(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() < 0 && std::isfinite(testcases[i].imag()))
         {
             assert(r.real() == 0);
             assert(!std::signbit(r.real()));
             assert(std::isinf(r.imag()));
-            assert(std::signbit(x[i].imag()) == std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) == std::signbit(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && x[i].real() > 0 && std::isfinite(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() > 0 && std::isfinite(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(r.real() > 0);
             assert(r.imag() == 0);
-            assert(std::signbit(x[i].imag()) == std::signbit(r.imag()));
+            assert(std::signbit(testcases[i].imag()) == std::signbit(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && x[i].real() < 0 && std::isnan(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() < 0 && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isinf(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && x[i].real() > 0 && std::isnan(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && testcases[i].real() > 0 && std::isnan(testcases[i].imag()))
         {
             assert(std::isinf(r.real()));
             assert(r.real() > 0);
             assert(std::isnan(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && (std::isfinite(x[i].imag()) || std::isnan(x[i].imag())))
+        else if (std::isnan(testcases[i].real()) && (std::isfinite(testcases[i].imag()) || std::isnan(testcases[i].imag())))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::signbit(x[i].imag()))
+        else if (std::signbit(testcases[i].imag()))
         {
             assert(!std::signbit(r.real()));
             assert(std::signbit(r.imag()));
diff --git a/test/std/numerics/complex.number/complex.transcendentals/tan.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/tan.pass.cpp
index 881427600686..041a7814d033 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/tan.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/tan.pass.cpp
@@ -37,11 +37,11 @@ void test_edges()
 {
     typedef std::complex<double> C;
     const double pi = std::atan2(+0., -0.);
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        std::complex<double> r = tan(x[i]);
-        std::complex<double> t1(-imag(x[i]), real(x[i]));
+        std::complex<double> r = tan(testcases[i]);
+        std::complex<double> t1(-imag(testcases[i]), real(testcases[i]));
         std::complex<double> t2 = tanh(t1);
         std::complex<double> z(imag(t2), -real(t2));
         if (std::isnan(real(r)))
diff --git a/test/std/numerics/complex.number/complex.transcendentals/tanh.pass.cpp b/test/std/numerics/complex.number/complex.transcendentals/tanh.pass.cpp
index 907c0e64dba9..9a2276a8b753 100644
--- a/test/std/numerics/complex.number/complex.transcendentals/tanh.pass.cpp
+++ b/test/std/numerics/complex.number/complex.transcendentals/tanh.pass.cpp
@@ -36,55 +36,55 @@ void test_edges()
 {
     typedef std::complex<double> C;
     const double pi = std::atan2(+0., -0.);
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        std::complex<double> r = tanh(x[i]);
-        if (x[i].real() == 0 && x[i].imag() == 0)
+        std::complex<double> r = tanh(testcases[i]);
+        if (testcases[i].real() == 0 && testcases[i].imag() == 0)
         {
             assert(r.real() == 0);
-            assert(std::signbit(r.real()) == std::signbit(x[i].real()));
+            assert(std::signbit(r.real()) == std::signbit(testcases[i].real()));
             assert(r.imag() == 0);
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
-        else if (std::isfinite(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isfinite(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isfinite(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isinf(x[i].real()) && std::isfinite(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isfinite(testcases[i].imag()))
         {
             assert(r.real() == 1);
             assert(r.imag() == 0);
-            assert(std::signbit(r.imag()) == std::signbit(sin(2*x[i].imag())));
+            assert(std::signbit(r.imag()) == std::signbit(sin(2*testcases[i].imag())));
         }
-        else if (std::isinf(x[i].real()) && std::isinf(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isinf(testcases[i].imag()))
         {
             assert(r.real() == 1);
             assert(r.imag() == 0);
         }
-        else if (std::isinf(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isinf(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(r.real() == 1);
             assert(r.imag() == 0);
         }
-        else if (std::isnan(x[i].real()) && x[i].imag() == 0)
+        else if (std::isnan(testcases[i].real()) && testcases[i].imag() == 0)
         {
             assert(std::isnan(r.real()));
             assert(r.imag() == 0);
-            assert(std::signbit(r.imag()) == std::signbit(x[i].imag()));
+            assert(std::signbit(r.imag()) == std::signbit(testcases[i].imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isfinite(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isfinite(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
         }
-        else if (std::isnan(x[i].real()) && std::isnan(x[i].imag()))
+        else if (std::isnan(testcases[i].real()) && std::isnan(testcases[i].imag()))
         {
             assert(std::isnan(r.real()));
             assert(std::isnan(r.imag()));
diff --git a/test/std/numerics/complex.number/complex.value.ops/abs.pass.cpp b/test/std/numerics/complex.number/complex.value.ops/abs.pass.cpp
index 5d841d6ee9f1..7a0e3bd70072 100644
--- a/test/std/numerics/complex.number/complex.value.ops/abs.pass.cpp
+++ b/test/std/numerics/complex.number/complex.value.ops/abs.pass.cpp
@@ -28,11 +28,11 @@ test()
 
 void test_edges()
 {
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        double r = abs(x[i]);
-        switch (classify(x[i]))
+        double r = abs(testcases[i]);
+        switch (classify(testcases[i]))
         {
         case zero:
             assert(r == 0);
diff --git a/test/std/numerics/complex.number/complex.value.ops/arg.pass.cpp b/test/std/numerics/complex.number/complex.value.ops/arg.pass.cpp
index a7da456b979c..78f2781b76e2 100644
--- a/test/std/numerics/complex.number/complex.value.ops/arg.pass.cpp
+++ b/test/std/numerics/complex.number/complex.value.ops/arg.pass.cpp
@@ -29,42 +29,42 @@ test()
 void test_edges()
 {
     const double pi = std::atan2(+0., -0.);
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        double r = arg(x[i]);
-        if (std::isnan(x[i].real()) || std::isnan(x[i].imag()))
+        double r = arg(testcases[i]);
+        if (std::isnan(testcases[i].real()) || std::isnan(testcases[i].imag()))
             assert(std::isnan(r));
         else
         {
-            switch (classify(x[i]))
+            switch (classify(testcases[i]))
             {
             case zero:
-                if (std::signbit(x[i].real()))
+                if (std::signbit(testcases[i].real()))
                 {
-                    if (std::signbit(x[i].imag()))
+                    if (std::signbit(testcases[i].imag()))
                         is_about(r, -pi);
                     else
                         is_about(r, pi);
                 }
                 else
                 {
-                    assert(std::signbit(x[i].imag()) == std::signbit(r));
+                    assert(std::signbit(testcases[i].imag()) == std::signbit(r));
                 }
                 break;
             case non_zero:
-                if (x[i].real() == 0)
+                if (testcases[i].real() == 0)
                 {
-                    if (x[i].imag() < 0)
+                    if (testcases[i].imag() < 0)
                         is_about(r, -pi/2);
                     else
                         is_about(r, pi/2);
                 }
-                else if (x[i].imag() == 0)
+                else if (testcases[i].imag() == 0)
                 {
-                    if (x[i].real() < 0)
+                    if (testcases[i].real() < 0)
                     {
-                        if (std::signbit(x[i].imag()))
+                        if (std::signbit(testcases[i].imag()))
                             is_about(r, -pi);
                         else
                             is_about(r, pi);
@@ -72,37 +72,37 @@ void test_edges()
                     else
                     {
                         assert(r == 0);
-                        assert(std::signbit(x[i].imag()) == std::signbit(r));
+                        assert(std::signbit(testcases[i].imag()) == std::signbit(r));
                     }
                 }
-                else if (x[i].imag() > 0)
+                else if (testcases[i].imag() > 0)
                     assert(r > 0);
                 else
                     assert(r < 0);
                 break;
             case inf:
-                if (std::isinf(x[i].real()) && std::isinf(x[i].imag()))
+                if (std::isinf(testcases[i].real()) && std::isinf(testcases[i].imag()))
                 {
-                    if (x[i].real() < 0)
+                    if (testcases[i].real() < 0)
                     {
-                        if (x[i].imag() > 0)
+                        if (testcases[i].imag() > 0)
                             is_about(r, 0.75 * pi);
                         else
                             is_about(r, -0.75 * pi);
                     }
                     else
                     {
-                        if (x[i].imag() > 0)
+                        if (testcases[i].imag() > 0)
                             is_about(r, 0.25 * pi);
                         else
                             is_about(r, -0.25 * pi);
                     }
                 }
-                else if (std::isinf(x[i].real()))
+                else if (std::isinf(testcases[i].real()))
                 {
-                    if (x[i].real() < 0)
+                    if (testcases[i].real() < 0)
                     {
-                        if (std::signbit(x[i].imag()))
+                        if (std::signbit(testcases[i].imag()))
                             is_about(r, -pi);
                         else
                             is_about(r, pi);
@@ -110,12 +110,12 @@ void test_edges()
                     else
                     {
                         assert(r == 0);
-                        assert(std::signbit(r) == std::signbit(x[i].imag()));
+                        assert(std::signbit(r) == std::signbit(testcases[i].imag()));
                     }
                 }
                 else
                 {
-                    if (x[i].imag() < 0)
+                    if (testcases[i].imag() < 0)
                         is_about(r, -pi/2);
                     else
                         is_about(r, pi/2);
diff --git a/test/std/numerics/complex.number/complex.value.ops/norm.pass.cpp b/test/std/numerics/complex.number/complex.value.ops/norm.pass.cpp
index 48f774e8e1c9..da7ad14bedce 100644
--- a/test/std/numerics/complex.number/complex.value.ops/norm.pass.cpp
+++ b/test/std/numerics/complex.number/complex.value.ops/norm.pass.cpp
@@ -28,11 +28,11 @@ test()
 
 void test_edges()
 {
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        double r = norm(x[i]);
-        switch (classify(x[i]))
+        double r = norm(testcases[i]);
+        switch (classify(testcases[i]))
         {
         case zero:
             assert(r == 0);
diff --git a/test/std/numerics/complex.number/complex.value.ops/polar.pass.cpp b/test/std/numerics/complex.number/complex.value.ops/polar.pass.cpp
index a8747bd7c83b..5e6cb0d523c2 100644
--- a/test/std/numerics/complex.number/complex.value.ops/polar.pass.cpp
+++ b/test/std/numerics/complex.number/complex.value.ops/polar.pass.cpp
@@ -46,11 +46,11 @@ test()
 
 void test_edges()
 {
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        double r = real(x[i]);
-        double theta = imag(x[i]);
+        double r = real(testcases[i]);
+        double theta = imag(testcases[i]);
         std::complex<double> z = std::polar(r, theta);
         switch (classify(r))
         {
diff --git a/test/std/numerics/complex.number/complex.value.ops/proj.pass.cpp b/test/std/numerics/complex.number/complex.value.ops/proj.pass.cpp
index 10bf7f8576f6..1a7e0c53f3d3 100644
--- a/test/std/numerics/complex.number/complex.value.ops/proj.pass.cpp
+++ b/test/std/numerics/complex.number/complex.value.ops/proj.pass.cpp
@@ -37,26 +37,26 @@ test()
 
 void test_edges()
 {
-    const unsigned N = sizeof(x) / sizeof(x[0]);
+    const unsigned N = sizeof(testcases) / sizeof(testcases[0]);
     for (unsigned i = 0; i < N; ++i)
     {
-        std::complex<double> r = proj(x[i]);
-        switch (classify(x[i]))
+        std::complex<double> r = proj(testcases[i]);
+        switch (classify(testcases[i]))
         {
         case zero:
         case non_zero:
-            assert(r == x[i]);
-            assert(std::signbit(real(r)) == std::signbit(real(x[i])));
-            assert(std::signbit(imag(r)) == std::signbit(imag(x[i])));
+            assert(r == testcases[i]);
+            assert(std::signbit(real(r)) == std::signbit(real(testcases[i])));
+            assert(std::signbit(imag(r)) == std::signbit(imag(testcases[i])));
             break;
         case inf:
             assert(std::isinf(real(r)) && real(r) > 0);
             assert(imag(r) == 0);
-            assert(std::signbit(imag(r)) == std::signbit(imag(x[i])));
+            assert(std::signbit(imag(r)) == std::signbit(imag(testcases[i])));
             break;
         case NaN:
         case non_zero_nan:
-            assert(classify(r) == classify(x[i]));
+            assert(classify(r) == classify(testcases[i]));
             break;
         }
     }
diff --git a/test/std/numerics/complex.number/version.pass.cpp b/test/std/numerics/complex.number/version.pass.cpp
deleted file mode 100644
index 316cfec739a9..000000000000
--- a/test/std/numerics/complex.number/version.pass.cpp
+++ /dev/null
@@ -1,20 +0,0 @@
-//===----------------------------------------------------------------------===//
-//
-//                     The LLVM Compiler Infrastructure
-//
-// This file is dual licensed under the MIT and the University of Illinois Open
-// Source Licenses. See LICENSE.TXT for details.
-//
-//===----------------------------------------------------------------------===//
-
-// <complex>
-
-#include <complex>
-
-#ifndef _LIBCPP_VERSION
-#error _LIBCPP_VERSION not defined
-#endif
-
-int main()
-{
-}
diff --git a/test/std/numerics/numarray/template.valarray/valarray.unary/not.pass.cpp b/test/std/numerics/numarray/template.valarray/valarray.unary/not.pass.cpp
index 0b792c68fb94..306ea0c18470 100644
--- a/test/std/numerics/numarray/template.valarray/valarray.unary/not.pass.cpp
+++ b/test/std/numerics/numarray/template.valarray/valarray.unary/not.pass.cpp
@@ -36,6 +36,6 @@ int main()
         std::valarray<bool> v2 = !(v + v);
         assert(v2.size() == v.size());
         for (int i = 0; i < v2.size(); ++i)
-            assert(v2[i] == !2*v[i]);
+            assert(v2[i] == !(2 * v[i]));
     }
 }
diff --git a/test/std/numerics/numarray/version.pass.cpp b/test/std/numerics/numarray/version.pass.cpp
deleted file mode 100644
index 85457d4329ec..000000000000
--- a/test/std/numerics/numarray/version.pass.cpp
+++ /dev/null
@@ -1,20 +0,0 @@
-//===----------------------------------------------------------------------===//
-//
-//                     The LLVM Compiler Infrastructure
-//
-// This file is dual licensed under the MIT and the University of Illinois Open
-// Source Licenses. See LICENSE.TXT for details.
-//
-//===----------------------------------------------------------------------===//
-
-// <valarray>
-
-#include <valarray>
-
-#ifndef _LIBCPP_VERSION
-#error _LIBCPP_VERSION not defined
-#endif
-
-int main()
-{
-}
diff --git a/test/std/numerics/numeric.ops/version.pass.cpp b/test/std/numerics/numeric.ops/version.pass.cpp
deleted file mode 100644
index fb6e0a1063ce..000000000000
--- a/test/std/numerics/numeric.ops/version.pass.cpp
+++ /dev/null
@@ -1,20 +0,0 @@
-//===----------------------------------------------------------------------===//
-//
-//                     The LLVM Compiler Infrastructure
-//
-// This file is dual licensed under the MIT and the University of Illinois Open
-// Source Licenses. See LICENSE.TXT for details.
-//
-//===----------------------------------------------------------------------===//
-
-// <numeric>
-
-#include <numeric>
-
-#ifndef _LIBCPP_VERSION
-#error _LIBCPP_VERSION not defined
-#endif
-
-int main()
-{
-}
diff --git a/test/std/numerics/rand/rand.device/ctor.pass.cpp b/test/std/numerics/rand/rand.device/ctor.pass.cpp
index dfeccc81e30e..8c45bb19a0a6 100644
--- a/test/std/numerics/rand/rand.device/ctor.pass.cpp
+++ b/test/std/numerics/rand/rand.device/ctor.pass.cpp
@@ -22,7 +22,13 @@
 #include <random>
 #include <system_error>
 #include <cassert>
+
+#if !defined(_WIN32)
 #include <unistd.h>
+#endif
+
+#include "test_macros.h"
+
 
 bool is_valid_random_device(const std::string &token) {
 #if defined(_LIBCPP_USING_DEV_RANDOM)
@@ -40,33 +46,20 @@ void check_random_device_valid(const std::string &token) {
 void check_random_device_invalid(const std::string &token) {
   try {
     std::random_device r(token);
-    assert(false);
-  } catch (const std::system_error &e) {
+    LIBCPP_ASSERT(false);
+  } catch (const std::system_error&) {
   }
 }
 
-int main() {
-  { std::random_device r; }
 
+int main() {
   {
-    int ec;
-    ec = close(STDIN_FILENO);
-    assert(!ec);
-    ec = close(STDOUT_FILENO);
-    assert(!ec);
-    ec = close(STDERR_FILENO);
-    assert(!ec);
     std::random_device r;
   }
-
   {
     std::string token = "wrong file";
-    if (is_valid_random_device(token))
-      check_random_device_valid(token);
-    else
-      check_random_device_invalid(token);
+    check_random_device_invalid(token);
   }
-
   {
     std::string token = "/dev/urandom";
     if (is_valid_random_device(token))
@@ -74,7 +67,6 @@ int main() {
     else
       check_random_device_invalid(token);
   }
-
   {
     std::string token = "/dev/random";
     if (is_valid_random_device(token))
@@ -82,4 +74,19 @@ int main() {
     else
       check_random_device_invalid(token);
   }
+#if !defined(_WIN32)
+// Test that random_device(const string&) properly handles getting
+// a file descriptor with the value '0'. Do this by closing the standard
+// streams so that the descriptor '0' is available.
+  {
+    int ec;
+    ec = close(STDIN_FILENO);
+    assert(!ec);
+    ec = close(STDOUT_FILENO);
+    assert(!ec);
+    ec = close(STDERR_FILENO);
+    assert(!ec);
+    std::random_device r;
+  }
+#endif // !defined(_WIN32)
 }
diff --git a/test/std/numerics/rand/rand.device/eval.pass.cpp b/test/std/numerics/rand/rand.device/eval.pass.cpp
index ed5361fbde75..eabcc201e068 100644
--- a/test/std/numerics/rand/rand.device/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.device/eval.pass.cpp
@@ -17,6 +17,8 @@
 #include <random>
 #include <cassert>
 
+#include "test_macros.h"
+
 int main()
 {
     {
@@ -28,9 +30,9 @@ int main()
     {
         std::random_device r("/dev/null");
         r();
-        assert(false);
+        LIBCPP_ASSERT(false);
     }
-    catch (const std::system_error& e)
+    catch (const std::system_error&)
     {
     }
 }
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval.pass.cpp
index f071e8507478..b267c2477e91 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval.pass.cpp
@@ -44,10 +44,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -80,10 +80,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval_param.pass.cpp
index e03fb57f380c..f96df82304f0 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval_param.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval_param.pass.cpp
@@ -46,10 +46,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -84,10 +84,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval.pass.cpp
index 43c6b546bdb2..88004ba4a741 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval.pass.cpp
@@ -29,447 +29,491 @@ sqr(T x)
     return x * x;
 }
 
-int main()
+void
+test1()
 {
+    typedef std::binomial_distribution<> D;
+    typedef std::mt19937_64 G;
+    G g;
+    D d(5, .75);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::binomial_distribution<> D;
-        typedef std::mt19937_64 G;
-        G g;
-        D d(5, .75);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = d.t() * d.p();
-        double x_var = x_mean*(1-d.p());
-        double x_skew = (1-2*d.p()) / std::sqrt(x_var);
-        double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.04);
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::binomial_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(30, .03125);
-        const int N = 100000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = d.t() * d.p();
-        double x_var = x_mean*(1-d.p());
-        double x_skew = (1-2*d.p()) / std::sqrt(x_var);
-        double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = d.t() * d.p();
+    double x_var = x_mean*(1-d.p());
+    double x_skew = (1-2*d.p()) / std::sqrt(x_var);
+    double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.04);
+}
+
+void
+test2()
+{
+    typedef std::binomial_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(30, .03125);
+    const int N = 100000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::binomial_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(40, .25);
-        const int N = 100000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = d.t() * d.p();
-        double x_var = x_mean*(1-d.p());
-        double x_skew = (1-2*d.p()) / std::sqrt(x_var);
-        double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.03);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.3);
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::binomial_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(40, 0);
-        const int N = 100000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        // In this case:
-        //   skew     computes to 0./0. == nan
-        //   kurtosis computes to 0./0. == nan
-        //   x_skew     == inf
-        //   x_kurtosis == inf
-        //   These tests are commented out because UBSan warns about division by 0
-//        skew /= u.size() * dev * var;
-//        kurtosis /= u.size() * var * var;
-//        kurtosis -= 3;
-        double x_mean = d.t() * d.p();
-        double x_var = x_mean*(1-d.p());
-//        double x_skew = (1-2*d.p()) / std::sqrt(x_var);
-//        double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
-        assert(mean == x_mean);
-        assert(var == x_var);
-//        assert(skew == x_skew);
-//        assert(kurtosis == x_kurtosis);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = d.t() * d.p();
+    double x_var = x_mean*(1-d.p());
+    double x_skew = (1-2*d.p()) / std::sqrt(x_var);
+    double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+}
+
+void
+test3()
+{
+    typedef std::binomial_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(40, .25);
+    const int N = 100000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::binomial_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(40, 1);
-        const int N = 100000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        // In this case:
-        //   skew     computes to 0./0. == nan
-        //   kurtosis computes to 0./0. == nan
-        //   x_skew     == -inf
-        //   x_kurtosis == inf
-        //   These tests are commented out because UBSan warns about division by 0
-//        skew /= u.size() * dev * var;
-//        kurtosis /= u.size() * var * var;
-//        kurtosis -= 3;
-        double x_mean = d.t() * d.p();
-        double x_var = x_mean*(1-d.p());
-//        double x_skew = (1-2*d.p()) / std::sqrt(x_var);
-//        double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
-        assert(mean == x_mean);
-        assert(var == x_var);
-//        assert(skew == x_skew);
-//        assert(kurtosis == x_kurtosis);
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::binomial_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(400, 0.5);
-        const int N = 100000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = d.t() * d.p();
-        double x_var = x_mean*(1-d.p());
-        double x_skew = (1-2*d.p()) / std::sqrt(x_var);
-        double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs(skew - x_skew) < 0.01);
-        assert(std::abs(kurtosis - x_kurtosis) < 0.01);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = d.t() * d.p();
+    double x_var = x_mean*(1-d.p());
+    double x_skew = (1-2*d.p()) / std::sqrt(x_var);
+    double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.03);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.3);
+}
+
+void
+test4()
+{
+    typedef std::binomial_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(40, 0);
+    const int N = 100000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::binomial_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(1, 0.5);
-        const int N = 100000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = d.t() * d.p();
-        double x_var = x_mean*(1-d.p());
-        double x_skew = (1-2*d.p()) / std::sqrt(x_var);
-        double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs(skew - x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        const int N = 100000;
-        std::mt19937 gen1;
-        std::mt19937 gen2;
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    // In this case:
+    //   skew     computes to 0./0. == nan
+    //   kurtosis computes to 0./0. == nan
+    //   x_skew     == inf
+    //   x_kurtosis == inf
+    //   These tests are commented out because UBSan warns about division by 0
+//    skew /= u.size() * dev * var;
+//    kurtosis /= u.size() * var * var;
+//    kurtosis -= 3;
+    double x_mean = d.t() * d.p();
+    double x_var = x_mean*(1-d.p());
+//    double x_skew = (1-2*d.p()) / std::sqrt(x_var);
+//    double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
+    assert(mean == x_mean);
+    assert(var == x_var);
+//    assert(skew == x_skew);
+//    assert(kurtosis == x_kurtosis);
+}
 
-        std::binomial_distribution<>         dist1(5, 0.1);
-        std::binomial_distribution<unsigned> dist2(5, 0.1);
+void
+test5()
+{
+    typedef std::binomial_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(40, 1);
+    const int N = 100000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    // In this case:
+    //   skew     computes to 0./0. == nan
+    //   kurtosis computes to 0./0. == nan
+    //   x_skew     == -inf
+    //   x_kurtosis == inf
+    //   These tests are commented out because UBSan warns about division by 0
+//    skew /= u.size() * dev * var;
+//    kurtosis /= u.size() * var * var;
+//    kurtosis -= 3;
+    double x_mean = d.t() * d.p();
+    double x_var = x_mean*(1-d.p());
+//    double x_skew = (1-2*d.p()) / std::sqrt(x_var);
+//    double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
+    assert(mean == x_mean);
+    assert(var == x_var);
+//    assert(skew == x_skew);
+//    assert(kurtosis == x_kurtosis);
+}
 
-        for(int i = 0; i < N; ++i)
-            assert(dist1(gen1) == dist2(gen2));
+void
+test6()
+{
+    typedef std::binomial_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(400, 0.5);
+    const int N = 100000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::binomial_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(0, 0.005);
-        const int N = 100000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        // In this case:
-        //   skew     computes to 0./0. == nan
-        //   kurtosis computes to 0./0. == nan
-        //   x_skew     == inf
-        //   x_kurtosis == inf
-        //   These tests are commented out because UBSan warns about division by 0
-//        skew /= u.size() * dev * var;
-//        kurtosis /= u.size() * var * var;
-//        kurtosis -= 3;
-        double x_mean = d.t() * d.p();
-        double x_var = x_mean*(1-d.p());
-//        double x_skew = (1-2*d.p()) / std::sqrt(x_var);
-//        double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
-        assert(mean == x_mean);
-        assert(var == x_var);
-//        assert(skew == x_skew);
-//        assert(kurtosis == x_kurtosis);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = d.t() * d.p();
+    double x_var = x_mean*(1-d.p());
+    double x_skew = (1-2*d.p()) / std::sqrt(x_var);
+    double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs(skew - x_skew) < 0.01);
+    assert(std::abs(kurtosis - x_kurtosis) < 0.01);
+}
+
+void
+test7()
+{
+    typedef std::binomial_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(1, 0.5);
+    const int N = 100000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::binomial_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(0, 0);
-        const int N = 100000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        // In this case:
-        //   skew     computes to 0./0. == nan
-        //   kurtosis computes to 0./0. == nan
-        //   x_skew     == inf
-        //   x_kurtosis == inf
-        //   These tests are commented out because UBSan warns about division by 0
-//        skew /= u.size() * dev * var;
-//        kurtosis /= u.size() * var * var;
-//        kurtosis -= 3;
-        double x_mean = d.t() * d.p();
-        double x_var = x_mean*(1-d.p());
-//        double x_skew = (1-2*d.p()) / std::sqrt(x_var);
-//        double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
-        assert(mean == x_mean);
-        assert(var == x_var);
-//        assert(skew == x_skew);
-//        assert(kurtosis == x_kurtosis);
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::binomial_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(0, 1);
-        const int N = 100000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        // In this case:
-        //   skew     computes to 0./0. == nan
-        //   kurtosis computes to 0./0. == nan
-        //   x_skew     == -inf
-        //   x_kurtosis == inf
-        //   These tests are commented out because UBSan warns about division by 0
-//        skew /= u.size() * dev * var;
-//        kurtosis /= u.size() * var * var;
-//        kurtosis -= 3;
-        double x_mean = d.t() * d.p();
-        double x_var = x_mean*(1-d.p());
-//        double x_skew = (1-2*d.p()) / std::sqrt(x_var);
-//        double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
-        assert(mean == x_mean);
-        assert(var == x_var);
-//        assert(skew == x_skew);
-//        assert(kurtosis == x_kurtosis);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = d.t() * d.p();
+    double x_var = x_mean*(1-d.p());
+    double x_skew = (1-2*d.p()) / std::sqrt(x_var);
+    double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs(skew - x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+}
+
+void
+test8()
+{
+    const int N = 100000;
+    std::mt19937 gen1;
+    std::mt19937 gen2;
+
+    std::binomial_distribution<>         dist1(5, 0.1);
+    std::binomial_distribution<unsigned> dist2(5, 0.1);
+
+    for(int i = 0; i < N; ++i)
+        assert(dist1(gen1) == dist2(gen2));
+}
+
+void
+test9()
+{
+    typedef std::binomial_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(0, 0.005);
+    const int N = 100000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    // In this case:
+    //   skew     computes to 0./0. == nan
+    //   kurtosis computes to 0./0. == nan
+    //   x_skew     == inf
+    //   x_kurtosis == inf
+    //   These tests are commented out because UBSan warns about division by 0
+//    skew /= u.size() * dev * var;
+//    kurtosis /= u.size() * var * var;
+//    kurtosis -= 3;
+    double x_mean = d.t() * d.p();
+    double x_var = x_mean*(1-d.p());
+//    double x_skew = (1-2*d.p()) / std::sqrt(x_var);
+//    double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
+    assert(mean == x_mean);
+    assert(var == x_var);
+//    assert(skew == x_skew);
+//    assert(kurtosis == x_kurtosis);
+}
+
+void
+test10()
+{
+    typedef std::binomial_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(0, 0);
+    const int N = 100000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    // In this case:
+    //   skew     computes to 0./0. == nan
+    //   kurtosis computes to 0./0. == nan
+    //   x_skew     == inf
+    //   x_kurtosis == inf
+    //   These tests are commented out because UBSan warns about division by 0
+//    skew /= u.size() * dev * var;
+//    kurtosis /= u.size() * var * var;
+//    kurtosis -= 3;
+    double x_mean = d.t() * d.p();
+    double x_var = x_mean*(1-d.p());
+//    double x_skew = (1-2*d.p()) / std::sqrt(x_var);
+//    double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
+    assert(mean == x_mean);
+    assert(var == x_var);
+//    assert(skew == x_skew);
+//    assert(kurtosis == x_kurtosis);
+}
+
+void
+test11()
+{
+    typedef std::binomial_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(0, 1);
+    const int N = 100000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    // In this case:
+    //   skew     computes to 0./0. == nan
+    //   kurtosis computes to 0./0. == nan
+    //   x_skew     == -inf
+    //   x_kurtosis == inf
+    //   These tests are commented out because UBSan warns about division by 0
+//    skew /= u.size() * dev * var;
+//    kurtosis /= u.size() * var * var;
+//    kurtosis -= 3;
+    double x_mean = d.t() * d.p();
+    double x_var = x_mean*(1-d.p());
+//    double x_skew = (1-2*d.p()) / std::sqrt(x_var);
+//    double x_kurtosis = (1-6*d.p()*(1-d.p())) / x_var;
+    assert(mean == x_mean);
+    assert(var == x_var);
+//    assert(skew == x_skew);
+//    assert(kurtosis == x_kurtosis);
+}
+
+int main()
+{
+    test1();
+    test2();
+    test3();
+    test4();
+    test5();
+    test6();
+    test7();
+    test8();
+    test9();
+    test10();
+    test11();
 }
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval_param.pass.cpp
index 1aa66ed57ad1..092a69778513 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval_param.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval_param.pass.cpp
@@ -53,10 +53,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -95,10 +95,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -137,10 +137,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval.pass.cpp
index a8ef221e3b67..4e9f9d3c044d 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval.pass.cpp
@@ -29,246 +29,270 @@ sqr(T x)
     return x * x;
 }
 
-int main()
+void
+test1()
+{
+    typedef std::geometric_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(.03125);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = (1 - d.p()) / d.p();
+    double x_var = x_mean / d.p();
+    double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
+    double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+}
+
+void
+test2()
+{
+    typedef std::geometric_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(0.05);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = (1 - d.p()) / d.p();
+    double x_var = x_mean / d.p();
+    double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
+    double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
+}
+
+void
+test3()
+{
+    typedef std::geometric_distribution<> D;
+    typedef std::minstd_rand G;
+    G g;
+    D d(.25);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = (1 - d.p()) / d.p();
+    double x_var = x_mean / d.p();
+    double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
+    double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
+}
+
+void
+test4()
 {
+    typedef std::geometric_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(0.5);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::geometric_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(.03125);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = (1 - d.p()) / d.p();
-        double x_var = x_mean / d.p();
-        double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
-        double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::geometric_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(0.05);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = (1 - d.p()) / d.p();
-        double x_var = x_mean / d.p();
-        double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
-        double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = (1 - d.p()) / d.p();
+    double x_var = x_mean / d.p();
+    double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
+    double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
+}
+
+void
+test5()
+{
+    typedef std::geometric_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(0.75);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::geometric_distribution<> D;
-        typedef std::minstd_rand G;
-        G g;
-        D d(.25);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = (1 - d.p()) / d.p();
-        double x_var = x_mean / d.p();
-        double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
-        double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::geometric_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(0.5);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = (1 - d.p()) / d.p();
-        double x_var = x_mean / d.p();
-        double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
-        double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = (1 - d.p()) / d.p();
+    double x_var = x_mean / d.p();
+    double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
+    double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
+}
+
+void
+test6()
+{
+    typedef std::geometric_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(0.96875);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::geometric_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(0.75);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = (1 - d.p()) / d.p();
-        double x_var = x_mean / d.p();
-        double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
-        double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::geometric_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(0.96875);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = (1 - d.p()) / d.p();
-        double x_var = x_mean / d.p();
-        double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
-        double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = (1 - d.p()) / d.p();
+    double x_var = x_mean / d.p();
+    double x_skew = (2 - d.p()) / std::sqrt((1 - d.p()));
+    double x_kurtosis = 6 + sqr(d.p()) / (1 - d.p());
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
+}
+
+int main()
+{
+    test1();
+    test2();
+    test3();
+    test4();
+    test5();
+    test6();
 }
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp
index 91dea8aa1337..c451f0130904 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp
@@ -53,10 +53,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -95,10 +95,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -137,10 +137,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval.pass.cpp
index 853161e9f9b7..929e6e7e6c3b 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval.pass.cpp
@@ -29,244 +29,268 @@ sqr(T x)
     return x * x;
 }
 
-int main()
+void
+test1()
+{
+    typedef std::negative_binomial_distribution<> D;
+    typedef std::minstd_rand G;
+    G g;
+    D d(5, .25);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = d.k() * (1 - d.p()) / d.p();
+    double x_var = x_mean / d.p();
+    double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
+    double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
+}
+
+void
+test2()
+{
+    typedef std::negative_binomial_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(30, .03125);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = d.k() * (1 - d.p()) / d.p();
+    double x_var = x_mean / d.p();
+    double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
+    double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+}
+
+void
+test3()
+{
+    typedef std::negative_binomial_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(40, .25);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = d.k() * (1 - d.p()) / d.p();
+    double x_var = x_mean / d.p();
+    double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
+    double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
+}
+
+void
+test4()
 {
+    typedef std::negative_binomial_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(40, 1);
+    const int N = 1000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::negative_binomial_distribution<> D;
-        typedef std::minstd_rand G;
-        G g;
-        D d(5, .25);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = d.k() * (1 - d.p()) / d.p();
-        double x_var = x_mean / d.p();
-        double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
-        double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::negative_binomial_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(30, .03125);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = d.k() * (1 - d.p()) / d.p();
-        double x_var = x_mean / d.p();
-        double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
-        double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = d.k() * (1 - d.p()) / d.p();
+    double x_var = x_mean / d.p();
+    double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
+    double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
+    assert(mean == x_mean);
+    assert(var == x_var);
+}
+
+void
+test5()
+{
+    typedef std::negative_binomial_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(400, 0.5);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::negative_binomial_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(40, .25);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = d.k() * (1 - d.p()) / d.p();
-        double x_var = x_mean / d.p();
-        double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
-        double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::negative_binomial_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(40, 1);
-        const int N = 1000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = d.k() * (1 - d.p()) / d.p();
-        double x_var = x_mean / d.p();
-        double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
-        double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
-        assert(mean == x_mean);
-        assert(var == x_var);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = d.k() * (1 - d.p()) / d.p();
+    double x_var = x_mean / d.p();
+    double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
+    double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.04);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.05);
+}
+
+void
+test6()
+{
+    typedef std::negative_binomial_distribution<> D;
+    typedef std::mt19937 G;
+    G g;
+    D d(1, 0.05);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::negative_binomial_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(400, 0.5);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = d.k() * (1 - d.p()) / d.p();
-        double x_var = x_mean / d.p();
-        double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
-        double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.04);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.05);
+        D::result_type v = d(g);
+        assert(d.min() <= v && v <= d.max());
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(),
+                                          double(0)) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::negative_binomial_distribution<> D;
-        typedef std::mt19937 G;
-        G g;
-        D d(1, 0.05);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v <= d.max());
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(),
-                                              double(0)) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = d.k() * (1 - d.p()) / d.p();
-        double x_var = x_mean / d.p();
-        double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
-        double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = d.k() * (1 - d.p()) / d.p();
+    double x_var = x_mean / d.p();
+    double x_skew = (2 - d.p()) / std::sqrt(d.k() * (1 - d.p()));
+    double x_kurtosis = 6. / d.k() + sqr(d.p()) / (d.k() * (1 - d.p()));
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
+}
+
+int main()
+{
+    test1();
+    test2();
+    test3();
+    test4();
+    test5();
+    test6();
 }
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval_param.pass.cpp
index f2f2a07879e2..2710061a1a05 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval_param.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval_param.pass.cpp
@@ -53,10 +53,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -95,10 +95,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -137,10 +137,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval.pass.cpp
index 6fbdd93f8ffd..f6bc3c73993c 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval.pass.cpp
@@ -51,10 +51,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -91,10 +91,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -131,10 +131,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval_param.pass.cpp
index 548848d19f3e..fd52a0488979 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval_param.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval_param.pass.cpp
@@ -52,10 +52,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -93,10 +93,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -134,10 +134,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval.pass.cpp
index 9b111cced8a8..2ad6784cd878 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval.pass.cpp
@@ -29,216 +29,236 @@ sqr(T x)
     return x * x;
 }
 
-int main()
+void
+test1()
+{
+    typedef std::lognormal_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d(-1./8192, 0.015625);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(v > 0);
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = std::exp(d.m() + sqr(d.s())/2);
+    double x_var = (std::exp(sqr(d.s())) - 1) * std::exp(2*d.m() + sqr(d.s()));
+    double x_skew = (std::exp(sqr(d.s())) + 2) *
+          std::sqrt((std::exp(sqr(d.s())) - 1));
+    double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) +
+                      3*std::exp(2*sqr(d.s())) - 6;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.05);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.25);
+}
+
+void
+test2()
 {
+    typedef std::lognormal_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d(-1./32, 0.25);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::lognormal_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d(-1./8192, 0.015625);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(v > 0);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = std::exp(d.m() + sqr(d.s())/2);
-        double x_var = (std::exp(sqr(d.s())) - 1) * std::exp(2*d.m() + sqr(d.s()));
-        double x_skew = (std::exp(sqr(d.s())) + 2) *
-              std::sqrt((std::exp(sqr(d.s())) - 1));
-        double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) +
-                          3*std::exp(2*sqr(d.s())) - 6;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.05);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.25);
+        D::result_type v = d(g);
+        assert(v > 0);
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::lognormal_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d(-1./32, 0.25);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(v > 0);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = std::exp(d.m() + sqr(d.s())/2);
-        double x_var = (std::exp(sqr(d.s())) - 1) * std::exp(2*d.m() + sqr(d.s()));
-        double x_skew = (std::exp(sqr(d.s())) + 2) *
-              std::sqrt((std::exp(sqr(d.s())) - 1));
-        double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) +
-                          3*std::exp(2*sqr(d.s())) - 6;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = std::exp(d.m() + sqr(d.s())/2);
+    double x_var = (std::exp(sqr(d.s())) - 1) * std::exp(2*d.m() + sqr(d.s()));
+    double x_skew = (std::exp(sqr(d.s())) + 2) *
+          std::sqrt((std::exp(sqr(d.s())) - 1));
+    double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) +
+                      3*std::exp(2*sqr(d.s())) - 6;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
+}
+
+void
+test3()
+{
+    typedef std::lognormal_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d(-1./8, 0.5);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::lognormal_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d(-1./8, 0.5);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(v > 0);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = std::exp(d.m() + sqr(d.s())/2);
-        double x_var = (std::exp(sqr(d.s())) - 1) * std::exp(2*d.m() + sqr(d.s()));
-        double x_skew = (std::exp(sqr(d.s())) + 2) *
-              std::sqrt((std::exp(sqr(d.s())) - 1));
-        double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) +
-                          3*std::exp(2*sqr(d.s())) - 6;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.02);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.05);
+        D::result_type v = d(g);
+        assert(v > 0);
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::lognormal_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d;
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(v > 0);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = std::exp(d.m() + sqr(d.s())/2);
-        double x_var = (std::exp(sqr(d.s())) - 1) * std::exp(2*d.m() + sqr(d.s()));
-        double x_skew = (std::exp(sqr(d.s())) + 2) *
-              std::sqrt((std::exp(sqr(d.s())) - 1));
-        double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) +
-                          3*std::exp(2*sqr(d.s())) - 6;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.02);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.08);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.4);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = std::exp(d.m() + sqr(d.s())/2);
+    double x_var = (std::exp(sqr(d.s())) - 1) * std::exp(2*d.m() + sqr(d.s()));
+    double x_skew = (std::exp(sqr(d.s())) + 2) *
+          std::sqrt((std::exp(sqr(d.s())) - 1));
+    double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) +
+                      3*std::exp(2*sqr(d.s())) - 6;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.02);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.05);
+}
+
+void
+test4()
+{
+    typedef std::lognormal_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d;
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::lognormal_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d(-0.78125, 1.25);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(v > 0);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = std::exp(d.m() + sqr(d.s())/2);
-        double x_var = (std::exp(sqr(d.s())) - 1) * std::exp(2*d.m() + sqr(d.s()));
-        double x_skew = (std::exp(sqr(d.s())) + 2) *
-              std::sqrt((std::exp(sqr(d.s())) - 1));
-        double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) +
-                          3*std::exp(2*sqr(d.s())) - 6;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.04);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.2);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.7);
+        D::result_type v = d(g);
+        assert(v > 0);
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = std::exp(d.m() + sqr(d.s())/2);
+    double x_var = (std::exp(sqr(d.s())) - 1) * std::exp(2*d.m() + sqr(d.s()));
+    double x_skew = (std::exp(sqr(d.s())) + 2) *
+          std::sqrt((std::exp(sqr(d.s())) - 1));
+    double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) +
+                      3*std::exp(2*sqr(d.s())) - 6;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.02);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.08);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.4);
+}
+
+void
+test5()
+{
+    typedef std::lognormal_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d(-0.78125, 1.25);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(v > 0);
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = std::exp(d.m() + sqr(d.s())/2);
+    double x_var = (std::exp(sqr(d.s())) - 1) * std::exp(2*d.m() + sqr(d.s()));
+    double x_skew = (std::exp(sqr(d.s())) + 2) *
+          std::sqrt((std::exp(sqr(d.s())) - 1));
+    double x_kurtosis = std::exp(4*sqr(d.s())) + 2*std::exp(3*sqr(d.s())) +
+                      3*std::exp(2*sqr(d.s())) - 6;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.04);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.2);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.7);
+}
+
+int main()
+{
+    test1();
+    test2();
+    test3();
+    test4();
+    test5();
 }
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval_param.pass.cpp
index 283403ea1a0d..8f397fcab096 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval_param.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval_param.pass.cpp
@@ -29,222 +29,241 @@ sqr(T x)
     return x * x;
 }
 
-int main()
+void
+test1()
 {
+    typedef std::lognormal_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d;
+    P p(-1./8192, 0.015625);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g, p);
+        assert(v > 0);
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = std::exp(p.m() + sqr(p.s())/2);
+    double x_var = (std::exp(sqr(p.s())) - 1) * std::exp(2*p.m() + sqr(p.s()));
+    double x_skew = (std::exp(sqr(p.s())) + 2) *
+          std::sqrt((std::exp(sqr(p.s())) - 1));
+    double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) +
+                      3*std::exp(2*sqr(p.s())) - 6;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.05);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.25);
+}
+
+void
+test2()
+{
+    typedef std::lognormal_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d;
+    P p(-1./32, 0.25);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g, p);
+        assert(v > 0);
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = std::exp(p.m() + sqr(p.s())/2);
+    double x_var = (std::exp(sqr(p.s())) - 1) * std::exp(2*p.m() + sqr(p.s()));
+    double x_skew = (std::exp(sqr(p.s())) + 2) *
+          std::sqrt((std::exp(sqr(p.s())) - 1));
+    double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) +
+                      3*std::exp(2*sqr(p.s())) - 6;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
+}
 
+void
+test3()
+{
+    typedef std::lognormal_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d;
+    P p(-1./8, 0.5);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::lognormal_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d;
-        P p(-1./8192, 0.015625);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g, p);
-            assert(v > 0);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = std::exp(p.m() + sqr(p.s())/2);
-        double x_var = (std::exp(sqr(p.s())) - 1) * std::exp(2*p.m() + sqr(p.s()));
-        double x_skew = (std::exp(sqr(p.s())) + 2) *
-              std::sqrt((std::exp(sqr(p.s())) - 1));
-        double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) +
-                          3*std::exp(2*sqr(p.s())) - 6;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.05);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.25);
+        D::result_type v = d(g, p);
+        assert(v > 0);
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::lognormal_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d;
-        P p(-1./32, 0.25);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g, p);
-            assert(v > 0);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = std::exp(p.m() + sqr(p.s())/2);
-        double x_var = (std::exp(sqr(p.s())) - 1) * std::exp(2*p.m() + sqr(p.s()));
-        double x_skew = (std::exp(sqr(p.s())) + 2) *
-              std::sqrt((std::exp(sqr(p.s())) - 1));
-        double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) +
-                          3*std::exp(2*sqr(p.s())) - 6;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = std::exp(p.m() + sqr(p.s())/2);
+    double x_var = (std::exp(sqr(p.s())) - 1) * std::exp(2*p.m() + sqr(p.s()));
+    double x_skew = (std::exp(sqr(p.s())) + 2) *
+          std::sqrt((std::exp(sqr(p.s())) - 1));
+    double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) +
+                      3*std::exp(2*sqr(p.s())) - 6;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.02);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.05);
+}
+
+void
+test4()
+{
+    typedef std::lognormal_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d(3, 4);
+    P p;
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::lognormal_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d;
-        P p(-1./8, 0.5);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g, p);
-            assert(v > 0);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = std::exp(p.m() + sqr(p.s())/2);
-        double x_var = (std::exp(sqr(p.s())) - 1) * std::exp(2*p.m() + sqr(p.s()));
-        double x_skew = (std::exp(sqr(p.s())) + 2) *
-              std::sqrt((std::exp(sqr(p.s())) - 1));
-        double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) +
-                          3*std::exp(2*sqr(p.s())) - 6;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.02);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.05);
+        D::result_type v = d(g, p);
+        assert(v > 0);
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::lognormal_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d(3, 4);
-        P p;
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g, p);
-            assert(v > 0);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = std::exp(p.m() + sqr(p.s())/2);
-        double x_var = (std::exp(sqr(p.s())) - 1) * std::exp(2*p.m() + sqr(p.s()));
-        double x_skew = (std::exp(sqr(p.s())) + 2) *
-              std::sqrt((std::exp(sqr(p.s())) - 1));
-        double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) +
-                          3*std::exp(2*sqr(p.s())) - 6;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.02);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.08);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.4);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = std::exp(p.m() + sqr(p.s())/2);
+    double x_var = (std::exp(sqr(p.s())) - 1) * std::exp(2*p.m() + sqr(p.s()));
+    double x_skew = (std::exp(sqr(p.s())) + 2) *
+          std::sqrt((std::exp(sqr(p.s())) - 1));
+    double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) +
+                      3*std::exp(2*sqr(p.s())) - 6;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.02);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.08);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.4);
+}
+
+void
+test5()
+{
+    typedef std::lognormal_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d;
+    P p(-0.78125, 1.25);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::lognormal_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d;
-        P p(-0.78125, 1.25);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g, p);
-            assert(v > 0);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = std::exp(p.m() + sqr(p.s())/2);
-        double x_var = (std::exp(sqr(p.s())) - 1) * std::exp(2*p.m() + sqr(p.s()));
-        double x_skew = (std::exp(sqr(p.s())) + 2) *
-              std::sqrt((std::exp(sqr(p.s())) - 1));
-        double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) +
-                          3*std::exp(2*sqr(p.s())) - 6;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.04);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.2);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.7);
+        D::result_type v = d(g, p);
+        assert(v > 0);
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = std::exp(p.m() + sqr(p.s())/2);
+    double x_var = (std::exp(sqr(p.s())) - 1) * std::exp(2*p.m() + sqr(p.s()));
+    double x_skew = (std::exp(sqr(p.s())) + 2) *
+          std::sqrt((std::exp(sqr(p.s())) - 1));
+    double x_kurtosis = std::exp(4*sqr(p.s())) + 2*std::exp(3*sqr(p.s())) +
+                      3*std::exp(2*sqr(p.s())) - 6;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.04);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.2);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.7);
+}
+
+int main()
+{
+    test1();
+    test2();
+    test3();
+    test4();
+    test5();
 }
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval.pass.cpp
index 95d0272dbc32..69f786397711 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval.pass.cpp
@@ -47,10 +47,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval_param.pass.cpp
index 20c3a44f13e1..af9c547cb7f9 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval_param.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval_param.pass.cpp
@@ -48,10 +48,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval.pass.cpp
index ef6b37e9f9cc..9210e8a8d350 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval.pass.cpp
@@ -47,10 +47,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -83,10 +83,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -119,10 +119,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval_param.pass.cpp
index 70bc29e3ad13..93053f0a36b7 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval_param.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval_param.pass.cpp
@@ -48,10 +48,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -85,10 +85,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -122,10 +122,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval.pass.cpp
index b2fe52676e7e..42965b0e6ab2 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval.pass.cpp
@@ -51,10 +51,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -91,10 +91,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -131,10 +131,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval_param.pass.cpp
index 9879e63a33e9..e7de18fdb434 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval_param.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval_param.pass.cpp
@@ -52,10 +52,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval.pass.cpp
index 6390acef8941..3f1b331889e5 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval.pass.cpp
@@ -29,162 +29,178 @@ sqr(T x)
     return x * x;
 }
 
-int main()
+void
+test1()
+{
+    typedef std::extreme_value_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d(0.5, 2);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = d.a() + d.b() * 0.577215665;
+    double x_var = sqr(d.b()) * 1.644934067;
+    double x_skew = 1.139547;
+    double x_kurtosis = 12./5;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+}
+
+void
+test2()
+{
+    typedef std::extreme_value_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d(1, 2);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = d.a() + d.b() * 0.577215665;
+    double x_var = sqr(d.b()) * 1.644934067;
+    double x_skew = 1.139547;
+    double x_kurtosis = 12./5;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+}
+
+void
+test3()
 {
+    typedef std::extreme_value_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d(1.5, 3);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::extreme_value_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d(0.5, 2);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = d.a() + d.b() * 0.577215665;
-        double x_var = sqr(d.b()) * 1.644934067;
-        double x_skew = 1.139547;
-        double x_kurtosis = 12./5;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+        D::result_type v = d(g);
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::extreme_value_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d(1, 2);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = d.a() + d.b() * 0.577215665;
-        double x_var = sqr(d.b()) * 1.644934067;
-        double x_skew = 1.139547;
-        double x_kurtosis = 12./5;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = d.a() + d.b() * 0.577215665;
+    double x_var = sqr(d.b()) * 1.644934067;
+    double x_skew = 1.139547;
+    double x_kurtosis = 12./5;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+}
+
+void
+test4()
+{
+    typedef std::extreme_value_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d(3, 4);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::extreme_value_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d(1.5, 3);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = d.a() + d.b() * 0.577215665;
-        double x_var = sqr(d.b()) * 1.644934067;
-        double x_skew = 1.139547;
-        double x_kurtosis = 12./5;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+        D::result_type v = d(g);
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::extreme_value_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d(3, 4);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = d.a() + d.b() * 0.577215665;
-        double x_var = sqr(d.b()) * 1.644934067;
-        double x_skew = 1.139547;
-        double x_kurtosis = 12./5;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = d.a() + d.b() * 0.577215665;
+    double x_var = sqr(d.b()) * 1.644934067;
+    double x_skew = 1.139547;
+    double x_kurtosis = 12./5;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+}
+
+int main()
+{
+    test1();
+    test2();
+    test3();
+    test4();
 }
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval_param.pass.cpp
index 6152cce8f4f8..21bf774228f8 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval_param.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval_param.pass.cpp
@@ -29,166 +29,182 @@ sqr(T x)
     return x * x;
 }
 
-int main()
+void
+test1()
+{
+    typedef std::extreme_value_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d(-0.5, 1);
+    P p(0.5, 2);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g, p);
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = p.a() + p.b() * 0.577215665;
+    double x_var = sqr(p.b()) * 1.644934067;
+    double x_skew = 1.139547;
+    double x_kurtosis = 12./5;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+}
+
+void
+test2()
+{
+    typedef std::extreme_value_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d(-0.5, 1);
+    P p(1, 2);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g, p);
+        u.push_back(v);
+    }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
+    {
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
+    }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = p.a() + p.b() * 0.577215665;
+    double x_var = sqr(p.b()) * 1.644934067;
+    double x_skew = 1.139547;
+    double x_kurtosis = 12./5;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+}
+
+void
+test3()
 {
+    typedef std::extreme_value_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d(-0.5, 1);
+    P p(1.5, 3);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::extreme_value_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d(-0.5, 1);
-        P p(0.5, 2);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g, p);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = p.a() + p.b() * 0.577215665;
-        double x_var = sqr(p.b()) * 1.644934067;
-        double x_skew = 1.139547;
-        double x_kurtosis = 12./5;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+        D::result_type v = d(g, p);
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::extreme_value_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d(-0.5, 1);
-        P p(1, 2);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g, p);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = p.a() + p.b() * 0.577215665;
-        double x_var = sqr(p.b()) * 1.644934067;
-        double x_skew = 1.139547;
-        double x_kurtosis = 12./5;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = p.a() + p.b() * 0.577215665;
+    double x_var = sqr(p.b()) * 1.644934067;
+    double x_skew = 1.139547;
+    double x_kurtosis = 12./5;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+}
+
+void
+test4()
+{
+    typedef std::extreme_value_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937 G;
+    G g;
+    D d(-0.5, 1);
+    P p(3, 4);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::extreme_value_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d(-0.5, 1);
-        P p(1.5, 3);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g, p);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = p.a() + p.b() * 0.577215665;
-        double x_var = sqr(p.b()) * 1.644934067;
-        double x_skew = 1.139547;
-        double x_kurtosis = 12./5;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+        D::result_type v = d(g, p);
+        u.push_back(v);
     }
+    double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
+    double var = 0;
+    double skew = 0;
+    double kurtosis = 0;
+    for (int i = 0; i < u.size(); ++i)
     {
-        typedef std::extreme_value_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937 G;
-        G g;
-        D d(-0.5, 1);
-        P p(3, 4);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g, p);
-            u.push_back(v);
-        }
-        double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
-        double var = 0;
-        double skew = 0;
-        double kurtosis = 0;
-        for (int i = 0; i < u.size(); ++i)
-        {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
-            var += d2;
-            skew += d * d2;
-            kurtosis += d2 * d2;
-        }
-        var /= u.size();
-        double dev = std::sqrt(var);
-        skew /= u.size() * dev * var;
-        kurtosis /= u.size() * var * var;
-        kurtosis -= 3;
-        double x_mean = p.a() + p.b() * 0.577215665;
-        double x_var = sqr(p.b()) * 1.644934067;
-        double x_skew = 1.139547;
-        double x_kurtosis = 12./5;
-        assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-        assert(std::abs((var - x_var) / x_var) < 0.01);
-        assert(std::abs((skew - x_skew) / x_skew) < 0.01);
-        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+        double dbl = (u[i] - mean);
+        double d2 = sqr(dbl);
+        var += d2;
+        skew += dbl * d2;
+        kurtosis += d2 * d2;
     }
+    var /= u.size();
+    double dev = std::sqrt(var);
+    skew /= u.size() * dev * var;
+    kurtosis /= u.size() * var * var;
+    kurtosis -= 3;
+    double x_mean = p.a() + p.b() * 0.577215665;
+    double x_var = sqr(p.b()) * 1.644934067;
+    double x_skew = 1.139547;
+    double x_kurtosis = 12./5;
+    assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+    assert(std::abs((var - x_var) / x_var) < 0.01);
+    assert(std::abs((skew - x_skew) / x_skew) < 0.01);
+    assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+}
+
+int main()
+{
+    test1();
+    test2();
+    test3();
+    test4();
 }
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval.pass.cpp
index 7c26cc8a1c47..7c23630ed1e1 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval.pass.cpp
@@ -51,10 +51,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -91,10 +91,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -131,10 +131,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval_param.pass.cpp
index 8ed39df819d7..54a89b6b3f40 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval_param.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval_param.pass.cpp
@@ -52,10 +52,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -93,10 +93,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -134,10 +134,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval.pass.cpp
index f5598978bf0a..a475624a58a8 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval.pass.cpp
@@ -50,10 +50,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -89,10 +89,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -128,10 +128,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval_param.pass.cpp
index c3bbdeb0ed6c..d24fbd9f9cf5 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval_param.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval_param.pass.cpp
@@ -52,10 +52,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -93,10 +93,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -134,10 +134,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval.pass.cpp
index e414932dc870..cfec8c0d81e1 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval.pass.cpp
@@ -51,10 +51,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -95,10 +95,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -139,10 +139,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval_param.pass.cpp
index 6da705eb26c7..a19654dbd575 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval_param.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval_param.pass.cpp
@@ -52,10 +52,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -97,10 +97,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -142,10 +142,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval.pass.cpp
index 5d14b3612b2e..3111912ec29c 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval.pass.cpp
@@ -20,6 +20,7 @@
 #include <vector>
 #include <iterator>
 #include <numeric>
+#include <algorithm>   // for sort
 #include <cassert>
 
 template <class T>
@@ -30,666 +31,710 @@ sqr(T x)
     return x*x;
 }
 
-int main()
+void
+test1()
 {
+    typedef std::piecewise_constant_distribution<> D;
+    typedef std::mt19937_64 G;
+    G g;
+    double b[] = {10, 14, 16, 17};
+    double p[] = {25, 62.5, 12.5};
+    const size_t Np = sizeof(p) / sizeof(p[0]);
+    D d(b, b+Np+1, p);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::piecewise_constant_distribution<> D;
-        typedef std::mt19937_64 G;
-        G g;
-        double b[] = {10, 14, 16, 17};
-        double p[] = {25, 62.5, 12.5};
-        const size_t Np = sizeof(p) / sizeof(p[0]);
-        D d(b, b+Np+1, p);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v < d.max());
-            u.push_back(v);
-        }
-        std::vector<double> prob(std::begin(p), std::end(p));
-        double s = std::accumulate(prob.begin(), prob.end(), 0.0);
-        for (int i = 0; i < prob.size(); ++i)
-            prob[i] /= s;
-        std::sort(u.begin(), u.end());
-        for (int i = 0; i < Np; ++i)
+        D::result_type v = d(g);
+        assert(d.min() <= v && v < d.max());
+        u.push_back(v);
+    }
+    std::vector<double> prob(std::begin(p), std::end(p));
+    double s = std::accumulate(prob.begin(), prob.end(), 0.0);
+    for (int i = 0; i < prob.size(); ++i)
+        prob[i] /= s;
+    std::sort(u.begin(), u.end());
+    for (int i = 0; i < Np; ++i)
+    {
+        typedef std::vector<D::result_type>::iterator I;
+        I lb = std::lower_bound(u.begin(), u.end(), b[i]);
+        I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
+        const size_t Ni = ub - lb;
+        if (prob[i] == 0)
+            assert(Ni == 0);
+        else
         {
-            typedef std::vector<D::result_type>::iterator I;
-            I lb = std::lower_bound(u.begin(), u.end(), b[i]);
-            I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
-            const size_t Ni = ub - lb;
-            if (prob[i] == 0)
-                assert(Ni == 0);
-            else
+            assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
+            double mean = std::accumulate(lb, ub, 0.0) / Ni;
+            double var = 0;
+            double skew = 0;
+            double kurtosis = 0;
+            for (I j = lb; j != ub; ++j)
             {
-                assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
-                double mean = std::accumulate(lb, ub, 0.0) / Ni;
-                double var = 0;
-                double skew = 0;
-                double kurtosis = 0;
-                for (I j = lb; j != ub; ++j)
-                {
-                    double d = (*j - mean);
-                    double d2 = sqr(d);
-                    var += d2;
-                    skew += d * d2;
-                    kurtosis += d2 * d2;
-                }
-                var /= Ni;
-                double dev = std::sqrt(var);
-                skew /= Ni * dev * var;
-                kurtosis /= Ni * var * var;
-                kurtosis -= 3;
-                double x_mean = (b[i+1] + b[i]) / 2;
-                double x_var = sqr(b[i+1] - b[i]) / 12;
-                double x_skew = 0;
-                double x_kurtosis = -6./5;
-                assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-                assert(std::abs((var - x_var) / x_var) < 0.01);
-                assert(std::abs(skew - x_skew) < 0.01);
-                assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+                double dbl = (*j - mean);
+                double d2 = sqr(dbl);
+                var += d2;
+                skew += dbl * d2;
+                kurtosis += d2 * d2;
             }
+            var /= Ni;
+            double dev = std::sqrt(var);
+            skew /= Ni * dev * var;
+            kurtosis /= Ni * var * var;
+            kurtosis -= 3;
+            double x_mean = (b[i+1] + b[i]) / 2;
+            double x_var = sqr(b[i+1] - b[i]) / 12;
+            double x_skew = 0;
+            double x_kurtosis = -6./5;
+            assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+            assert(std::abs((var - x_var) / x_var) < 0.01);
+            assert(std::abs(skew - x_skew) < 0.01);
+            assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
         }
     }
+}
+
+void
+test2()
+{
+    typedef std::piecewise_constant_distribution<> D;
+    typedef std::mt19937_64 G;
+    G g;
+    double b[] = {10, 14, 16, 17};
+    double p[] = {0, 62.5, 12.5};
+    const size_t Np = sizeof(p) / sizeof(p[0]);
+    D d(b, b+Np+1, p);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::piecewise_constant_distribution<> D;
-        typedef std::mt19937_64 G;
-        G g;
-        double b[] = {10, 14, 16, 17};
-        double p[] = {0, 62.5, 12.5};
-        const size_t Np = sizeof(p) / sizeof(p[0]);
-        D d(b, b+Np+1, p);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v < d.max());
-            u.push_back(v);
-        }
-        std::vector<double> prob(std::begin(p), std::end(p));
-        double s = std::accumulate(prob.begin(), prob.end(), 0.0);
-        for (int i = 0; i < prob.size(); ++i)
-            prob[i] /= s;
-        std::sort(u.begin(), u.end());
-        for (int i = 0; i < Np; ++i)
+        D::result_type v = d(g);
+        assert(d.min() <= v && v < d.max());
+        u.push_back(v);
+    }
+    std::vector<double> prob(std::begin(p), std::end(p));
+    double s = std::accumulate(prob.begin(), prob.end(), 0.0);
+    for (int i = 0; i < prob.size(); ++i)
+        prob[i] /= s;
+    std::sort(u.begin(), u.end());
+    for (int i = 0; i < Np; ++i)
+    {
+        typedef std::vector<D::result_type>::iterator I;
+        I lb = std::lower_bound(u.begin(), u.end(), b[i]);
+        I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
+        const size_t Ni = ub - lb;
+        if (prob[i] == 0)
+            assert(Ni == 0);
+        else
         {
-            typedef std::vector<D::result_type>::iterator I;
-            I lb = std::lower_bound(u.begin(), u.end(), b[i]);
-            I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
-            const size_t Ni = ub - lb;
-            if (prob[i] == 0)
-                assert(Ni == 0);
-            else
+            assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
+            double mean = std::accumulate(lb, ub, 0.0) / Ni;
+            double var = 0;
+            double skew = 0;
+            double kurtosis = 0;
+            for (I j = lb; j != ub; ++j)
             {
-                assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
-                double mean = std::accumulate(lb, ub, 0.0) / Ni;
-                double var = 0;
-                double skew = 0;
-                double kurtosis = 0;
-                for (I j = lb; j != ub; ++j)
-                {
-                    double d = (*j - mean);
-                    double d2 = sqr(d);
-                    var += d2;
-                    skew += d * d2;
-                    kurtosis += d2 * d2;
-                }
-                var /= Ni;
-                double dev = std::sqrt(var);
-                skew /= Ni * dev * var;
-                kurtosis /= Ni * var * var;
-                kurtosis -= 3;
-                double x_mean = (b[i+1] + b[i]) / 2;
-                double x_var = sqr(b[i+1] - b[i]) / 12;
-                double x_skew = 0;
-                double x_kurtosis = -6./5;
-                assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-                assert(std::abs((var - x_var) / x_var) < 0.01);
-                assert(std::abs(skew - x_skew) < 0.01);
-                assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+                double dbl = (*j - mean);
+                double d2 = sqr(dbl);
+                var += d2;
+                skew += dbl * d2;
+                kurtosis += d2 * d2;
             }
+            var /= Ni;
+            double dev = std::sqrt(var);
+            skew /= Ni * dev * var;
+            kurtosis /= Ni * var * var;
+            kurtosis -= 3;
+            double x_mean = (b[i+1] + b[i]) / 2;
+            double x_var = sqr(b[i+1] - b[i]) / 12;
+            double x_skew = 0;
+            double x_kurtosis = -6./5;
+            assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+            assert(std::abs((var - x_var) / x_var) < 0.01);
+            assert(std::abs(skew - x_skew) < 0.01);
+            assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
         }
     }
+}
+
+void
+test3()
+{
+    typedef std::piecewise_constant_distribution<> D;
+    typedef std::mt19937_64 G;
+    G g;
+    double b[] = {10, 14, 16, 17};
+    double p[] = {25, 0, 12.5};
+    const size_t Np = sizeof(p) / sizeof(p[0]);
+    D d(b, b+Np+1, p);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v < d.max());
+        u.push_back(v);
+    }
+    std::vector<double> prob(std::begin(p), std::end(p));
+    double s = std::accumulate(prob.begin(), prob.end(), 0.0);
+    for (int i = 0; i < prob.size(); ++i)
+        prob[i] /= s;
+    std::sort(u.begin(), u.end());
+    for (int i = 0; i < Np; ++i)
     {
-        typedef std::piecewise_constant_distribution<> D;
-        typedef std::mt19937_64 G;
-        G g;
-        double b[] = {10, 14, 16, 17};
-        double p[] = {25, 0, 12.5};
-        const size_t Np = sizeof(p) / sizeof(p[0]);
-        D d(b, b+Np+1, p);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
+        typedef std::vector<D::result_type>::iterator I;
+        I lb = std::lower_bound(u.begin(), u.end(), b[i]);
+        I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
+        const size_t Ni = ub - lb;
+        if (prob[i] == 0)
+            assert(Ni == 0);
+        else
         {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v < d.max());
-            u.push_back(v);
-        }
-        std::vector<double> prob(std::begin(p), std::end(p));
-        double s = std::accumulate(prob.begin(), prob.end(), 0.0);
-        for (int i = 0; i < prob.size(); ++i)
-            prob[i] /= s;
-        std::sort(u.begin(), u.end());
-        for (int i = 0; i < Np; ++i)
-        {
-            typedef std::vector<D::result_type>::iterator I;
-            I lb = std::lower_bound(u.begin(), u.end(), b[i]);
-            I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
-            const size_t Ni = ub - lb;
-            if (prob[i] == 0)
-                assert(Ni == 0);
-            else
+            assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
+            double mean = std::accumulate(lb, ub, 0.0) / Ni;
+            double var = 0;
+            double skew = 0;
+            double kurtosis = 0;
+            for (I j = lb; j != ub; ++j)
             {
-                assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
-                double mean = std::accumulate(lb, ub, 0.0) / Ni;
-                double var = 0;
-                double skew = 0;
-                double kurtosis = 0;
-                for (I j = lb; j != ub; ++j)
-                {
-                    double d = (*j - mean);
-                    double d2 = sqr(d);
-                    var += d2;
-                    skew += d * d2;
-                    kurtosis += d2 * d2;
-                }
-                var /= Ni;
-                double dev = std::sqrt(var);
-                skew /= Ni * dev * var;
-                kurtosis /= Ni * var * var;
-                kurtosis -= 3;
-                double x_mean = (b[i+1] + b[i]) / 2;
-                double x_var = sqr(b[i+1] - b[i]) / 12;
-                double x_skew = 0;
-                double x_kurtosis = -6./5;
-                assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-                assert(std::abs((var - x_var) / x_var) < 0.01);
-                assert(std::abs(skew - x_skew) < 0.01);
-                assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+                double dbl = (*j - mean);
+                double d2 = sqr(dbl);
+                var += d2;
+                skew += dbl * d2;
+                kurtosis += d2 * d2;
             }
+            var /= Ni;
+            double dev = std::sqrt(var);
+            skew /= Ni * dev * var;
+            kurtosis /= Ni * var * var;
+            kurtosis -= 3;
+            double x_mean = (b[i+1] + b[i]) / 2;
+            double x_var = sqr(b[i+1] - b[i]) / 12;
+            double x_skew = 0;
+            double x_kurtosis = -6./5;
+            assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+            assert(std::abs((var - x_var) / x_var) < 0.01);
+            assert(std::abs(skew - x_skew) < 0.01);
+            assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
         }
     }
+}
+
+void
+test4()
+{
+    typedef std::piecewise_constant_distribution<> D;
+    typedef std::mt19937_64 G;
+    G g;
+    double b[] = {10, 14, 16, 17};
+    double p[] = {25, 62.5, 0};
+    const size_t Np = sizeof(p) / sizeof(p[0]);
+    D d(b, b+Np+1, p);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v < d.max());
+        u.push_back(v);
+    }
+    std::vector<double> prob(std::begin(p), std::end(p));
+    double s = std::accumulate(prob.begin(), prob.end(), 0.0);
+    for (int i = 0; i < prob.size(); ++i)
+        prob[i] /= s;
+    std::sort(u.begin(), u.end());
+    for (int i = 0; i < Np; ++i)
     {
-        typedef std::piecewise_constant_distribution<> D;
-        typedef std::mt19937_64 G;
-        G g;
-        double b[] = {10, 14, 16, 17};
-        double p[] = {25, 62.5, 0};
-        const size_t Np = sizeof(p) / sizeof(p[0]);
-        D d(b, b+Np+1, p);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v < d.max());
-            u.push_back(v);
-        }
-        std::vector<double> prob(std::begin(p), std::end(p));
-        double s = std::accumulate(prob.begin(), prob.end(), 0.0);
-        for (int i = 0; i < prob.size(); ++i)
-            prob[i] /= s;
-        std::sort(u.begin(), u.end());
-        for (int i = 0; i < Np; ++i)
+        typedef std::vector<D::result_type>::iterator I;
+        I lb = std::lower_bound(u.begin(), u.end(), b[i]);
+        I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
+        const size_t Ni = ub - lb;
+        if (prob[i] == 0)
+            assert(Ni == 0);
+        else
         {
-            typedef std::vector<D::result_type>::iterator I;
-            I lb = std::lower_bound(u.begin(), u.end(), b[i]);
-            I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
-            const size_t Ni = ub - lb;
-            if (prob[i] == 0)
-                assert(Ni == 0);
-            else
+            assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
+            double mean = std::accumulate(lb, ub, 0.0) / Ni;
+            double var = 0;
+            double skew = 0;
+            double kurtosis = 0;
+            for (I j = lb; j != ub; ++j)
             {
-                assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
-                double mean = std::accumulate(lb, ub, 0.0) / Ni;
-                double var = 0;
-                double skew = 0;
-                double kurtosis = 0;
-                for (I j = lb; j != ub; ++j)
-                {
-                    double d = (*j - mean);
-                    double d2 = sqr(d);
-                    var += d2;
-                    skew += d * d2;
-                    kurtosis += d2 * d2;
-                }
-                var /= Ni;
-                double dev = std::sqrt(var);
-                skew /= Ni * dev * var;
-                kurtosis /= Ni * var * var;
-                kurtosis -= 3;
-                double x_mean = (b[i+1] + b[i]) / 2;
-                double x_var = sqr(b[i+1] - b[i]) / 12;
-                double x_skew = 0;
-                double x_kurtosis = -6./5;
-                assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-                assert(std::abs((var - x_var) / x_var) < 0.01);
-                assert(std::abs(skew - x_skew) < 0.01);
-                assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+                double dbl = (*j - mean);
+                double d2 = sqr(dbl);
+                var += d2;
+                skew += dbl * d2;
+                kurtosis += d2 * d2;
             }
+            var /= Ni;
+            double dev = std::sqrt(var);
+            skew /= Ni * dev * var;
+            kurtosis /= Ni * var * var;
+            kurtosis -= 3;
+            double x_mean = (b[i+1] + b[i]) / 2;
+            double x_var = sqr(b[i+1] - b[i]) / 12;
+            double x_skew = 0;
+            double x_kurtosis = -6./5;
+            assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+            assert(std::abs((var - x_var) / x_var) < 0.01);
+            assert(std::abs(skew - x_skew) < 0.01);
+            assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
         }
     }
+}
+
+void
+test5()
+{
+    typedef std::piecewise_constant_distribution<> D;
+    typedef std::mt19937_64 G;
+    G g;
+    double b[] = {10, 14, 16, 17};
+    double p[] = {25, 0, 0};
+    const size_t Np = sizeof(p) / sizeof(p[0]);
+    D d(b, b+Np+1, p);
+    const int N = 100000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::piecewise_constant_distribution<> D;
-        typedef std::mt19937_64 G;
-        G g;
-        double b[] = {10, 14, 16, 17};
-        double p[] = {25, 0, 0};
-        const size_t Np = sizeof(p) / sizeof(p[0]);
-        D d(b, b+Np+1, p);
-        const int N = 100000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v < d.max());
-            u.push_back(v);
-        }
-        std::vector<double> prob(std::begin(p), std::end(p));
-        double s = std::accumulate(prob.begin(), prob.end(), 0.0);
-        for (int i = 0; i < prob.size(); ++i)
-            prob[i] /= s;
-        std::sort(u.begin(), u.end());
-        for (int i = 0; i < Np; ++i)
+        D::result_type v = d(g);
+        assert(d.min() <= v && v < d.max());
+        u.push_back(v);
+    }
+    std::vector<double> prob(std::begin(p), std::end(p));
+    double s = std::accumulate(prob.begin(), prob.end(), 0.0);
+    for (int i = 0; i < prob.size(); ++i)
+        prob[i] /= s;
+    std::sort(u.begin(), u.end());
+    for (int i = 0; i < Np; ++i)
+    {
+        typedef std::vector<D::result_type>::iterator I;
+        I lb = std::lower_bound(u.begin(), u.end(), b[i]);
+        I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
+        const size_t Ni = ub - lb;
+        if (prob[i] == 0)
+            assert(Ni == 0);
+        else
         {
-            typedef std::vector<D::result_type>::iterator I;
-            I lb = std::lower_bound(u.begin(), u.end(), b[i]);
-            I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
-            const size_t Ni = ub - lb;
-            if (prob[i] == 0)
-                assert(Ni == 0);
-            else
+            assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
+            double mean = std::accumulate(lb, ub, 0.0) / Ni;
+            double var = 0;
+            double skew = 0;
+            double kurtosis = 0;
+            for (I j = lb; j != ub; ++j)
             {
-                assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
-                double mean = std::accumulate(lb, ub, 0.0) / Ni;
-                double var = 0;
-                double skew = 0;
-                double kurtosis = 0;
-                for (I j = lb; j != ub; ++j)
-                {
-                    double d = (*j - mean);
-                    double d2 = sqr(d);
-                    var += d2;
-                    skew += d * d2;
-                    kurtosis += d2 * d2;
-                }
-                var /= Ni;
-                double dev = std::sqrt(var);
-                skew /= Ni * dev * var;
-                kurtosis /= Ni * var * var;
-                kurtosis -= 3;
-                double x_mean = (b[i+1] + b[i]) / 2;
-                double x_var = sqr(b[i+1] - b[i]) / 12;
-                double x_skew = 0;
-                double x_kurtosis = -6./5;
-                assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-                assert(std::abs((var - x_var) / x_var) < 0.01);
-                assert(std::abs(skew - x_skew) < 0.01);
-                assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+                double dbl = (*j - mean);
+                double d2 = sqr(dbl);
+                var += d2;
+                skew += dbl * d2;
+                kurtosis += d2 * d2;
             }
+            var /= Ni;
+            double dev = std::sqrt(var);
+            skew /= Ni * dev * var;
+            kurtosis /= Ni * var * var;
+            kurtosis -= 3;
+            double x_mean = (b[i+1] + b[i]) / 2;
+            double x_var = sqr(b[i+1] - b[i]) / 12;
+            double x_skew = 0;
+            double x_kurtosis = -6./5;
+            assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+            assert(std::abs((var - x_var) / x_var) < 0.01);
+            assert(std::abs(skew - x_skew) < 0.01);
+            assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
         }
     }
+}
+
+void
+test6()
+{
+    typedef std::piecewise_constant_distribution<> D;
+    typedef std::mt19937_64 G;
+    G g;
+    double b[] = {10, 14, 16, 17};
+    double p[] = {0, 25, 0};
+    const size_t Np = sizeof(p) / sizeof(p[0]);
+    D d(b, b+Np+1, p);
+    const int N = 100000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v < d.max());
+        u.push_back(v);
+    }
+    std::vector<double> prob(std::begin(p), std::end(p));
+    double s = std::accumulate(prob.begin(), prob.end(), 0.0);
+    for (int i = 0; i < prob.size(); ++i)
+        prob[i] /= s;
+    std::sort(u.begin(), u.end());
+    for (int i = 0; i < Np; ++i)
     {
-        typedef std::piecewise_constant_distribution<> D;
-        typedef std::mt19937_64 G;
-        G g;
-        double b[] = {10, 14, 16, 17};
-        double p[] = {0, 25, 0};
-        const size_t Np = sizeof(p) / sizeof(p[0]);
-        D d(b, b+Np+1, p);
-        const int N = 100000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v < d.max());
-            u.push_back(v);
-        }
-        std::vector<double> prob(std::begin(p), std::end(p));
-        double s = std::accumulate(prob.begin(), prob.end(), 0.0);
-        for (int i = 0; i < prob.size(); ++i)
-            prob[i] /= s;
-        std::sort(u.begin(), u.end());
-        for (int i = 0; i < Np; ++i)
+        typedef std::vector<D::result_type>::iterator I;
+        I lb = std::lower_bound(u.begin(), u.end(), b[i]);
+        I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
+        const size_t Ni = ub - lb;
+        if (prob[i] == 0)
+            assert(Ni == 0);
+        else
         {
-            typedef std::vector<D::result_type>::iterator I;
-            I lb = std::lower_bound(u.begin(), u.end(), b[i]);
-            I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
-            const size_t Ni = ub - lb;
-            if (prob[i] == 0)
-                assert(Ni == 0);
-            else
+            assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
+            double mean = std::accumulate(lb, ub, 0.0) / Ni;
+            double var = 0;
+            double skew = 0;
+            double kurtosis = 0;
+            for (I j = lb; j != ub; ++j)
             {
-                assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
-                double mean = std::accumulate(lb, ub, 0.0) / Ni;
-                double var = 0;
-                double skew = 0;
-                double kurtosis = 0;
-                for (I j = lb; j != ub; ++j)
-                {
-                    double d = (*j - mean);
-                    double d2 = sqr(d);
-                    var += d2;
-                    skew += d * d2;
-                    kurtosis += d2 * d2;
-                }
-                var /= Ni;
-                double dev = std::sqrt(var);
-                skew /= Ni * dev * var;
-                kurtosis /= Ni * var * var;
-                kurtosis -= 3;
-                double x_mean = (b[i+1] + b[i]) / 2;
-                double x_var = sqr(b[i+1] - b[i]) / 12;
-                double x_skew = 0;
-                double x_kurtosis = -6./5;
-                assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-                assert(std::abs((var - x_var) / x_var) < 0.01);
-                assert(std::abs(skew - x_skew) < 0.01);
-                assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+                double dbl = (*j - mean);
+                double d2 = sqr(dbl);
+                var += d2;
+                skew += dbl * d2;
+                kurtosis += d2 * d2;
             }
+            var /= Ni;
+            double dev = std::sqrt(var);
+            skew /= Ni * dev * var;
+            kurtosis /= Ni * var * var;
+            kurtosis -= 3;
+            double x_mean = (b[i+1] + b[i]) / 2;
+            double x_var = sqr(b[i+1] - b[i]) / 12;
+            double x_skew = 0;
+            double x_kurtosis = -6./5;
+            assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+            assert(std::abs((var - x_var) / x_var) < 0.01);
+            assert(std::abs(skew - x_skew) < 0.01);
+            assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
         }
     }
+}
+
+void
+test7()
+{
+    typedef std::piecewise_constant_distribution<> D;
+    typedef std::mt19937_64 G;
+    G g;
+    double b[] = {10, 14, 16, 17};
+    double p[] = {0, 0, 1};
+    const size_t Np = sizeof(p) / sizeof(p[0]);
+    D d(b, b+Np+1, p);
+    const int N = 100000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::piecewise_constant_distribution<> D;
-        typedef std::mt19937_64 G;
-        G g;
-        double b[] = {10, 14, 16, 17};
-        double p[] = {0, 0, 1};
-        const size_t Np = sizeof(p) / sizeof(p[0]);
-        D d(b, b+Np+1, p);
-        const int N = 100000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v < d.max());
-            u.push_back(v);
-        }
-        std::vector<double> prob(std::begin(p), std::end(p));
-        double s = std::accumulate(prob.begin(), prob.end(), 0.0);
-        for (int i = 0; i < prob.size(); ++i)
-            prob[i] /= s;
-        std::sort(u.begin(), u.end());
-        for (int i = 0; i < Np; ++i)
+        D::result_type v = d(g);
+        assert(d.min() <= v && v < d.max());
+        u.push_back(v);
+    }
+    std::vector<double> prob(std::begin(p), std::end(p));
+    double s = std::accumulate(prob.begin(), prob.end(), 0.0);
+    for (int i = 0; i < prob.size(); ++i)
+        prob[i] /= s;
+    std::sort(u.begin(), u.end());
+    for (int i = 0; i < Np; ++i)
+    {
+        typedef std::vector<D::result_type>::iterator I;
+        I lb = std::lower_bound(u.begin(), u.end(), b[i]);
+        I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
+        const size_t Ni = ub - lb;
+        if (prob[i] == 0)
+            assert(Ni == 0);
+        else
         {
-            typedef std::vector<D::result_type>::iterator I;
-            I lb = std::lower_bound(u.begin(), u.end(), b[i]);
-            I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
-            const size_t Ni = ub - lb;
-            if (prob[i] == 0)
-                assert(Ni == 0);
-            else
+            assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
+            double mean = std::accumulate(lb, ub, 0.0) / Ni;
+            double var = 0;
+            double skew = 0;
+            double kurtosis = 0;
+            for (I j = lb; j != ub; ++j)
             {
-                assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
-                double mean = std::accumulate(lb, ub, 0.0) / Ni;
-                double var = 0;
-                double skew = 0;
-                double kurtosis = 0;
-                for (I j = lb; j != ub; ++j)
-                {
-                    double d = (*j - mean);
-                    double d2 = sqr(d);
-                    var += d2;
-                    skew += d * d2;
-                    kurtosis += d2 * d2;
-                }
-                var /= Ni;
-                double dev = std::sqrt(var);
-                skew /= Ni * dev * var;
-                kurtosis /= Ni * var * var;
-                kurtosis -= 3;
-                double x_mean = (b[i+1] + b[i]) / 2;
-                double x_var = sqr(b[i+1] - b[i]) / 12;
-                double x_skew = 0;
-                double x_kurtosis = -6./5;
-                assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-                assert(std::abs((var - x_var) / x_var) < 0.01);
-                assert(std::abs(skew - x_skew) < 0.01);
-                assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+                double dbl = (*j - mean);
+                double d2 = sqr(dbl);
+                var += d2;
+                skew += dbl * d2;
+                kurtosis += d2 * d2;
             }
+            var /= Ni;
+            double dev = std::sqrt(var);
+            skew /= Ni * dev * var;
+            kurtosis /= Ni * var * var;
+            kurtosis -= 3;
+            double x_mean = (b[i+1] + b[i]) / 2;
+            double x_var = sqr(b[i+1] - b[i]) / 12;
+            double x_skew = 0;
+            double x_kurtosis = -6./5;
+            assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+            assert(std::abs((var - x_var) / x_var) < 0.01);
+            assert(std::abs(skew - x_skew) < 0.01);
+            assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
         }
     }
+}
+
+void
+test8()
+{
+    typedef std::piecewise_constant_distribution<> D;
+    typedef std::mt19937_64 G;
+    G g;
+    double b[] = {10, 14, 16};
+    double p[] = {75, 25};
+    const size_t Np = sizeof(p) / sizeof(p[0]);
+    D d(b, b+Np+1, p);
+    const int N = 100000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v < d.max());
+        u.push_back(v);
+    }
+    std::vector<double> prob(std::begin(p), std::end(p));
+    double s = std::accumulate(prob.begin(), prob.end(), 0.0);
+    for (int i = 0; i < prob.size(); ++i)
+        prob[i] /= s;
+    std::sort(u.begin(), u.end());
+    for (int i = 0; i < Np; ++i)
     {
-        typedef std::piecewise_constant_distribution<> D;
-        typedef std::mt19937_64 G;
-        G g;
-        double b[] = {10, 14, 16};
-        double p[] = {75, 25};
-        const size_t Np = sizeof(p) / sizeof(p[0]);
-        D d(b, b+Np+1, p);
-        const int N = 100000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
+        typedef std::vector<D::result_type>::iterator I;
+        I lb = std::lower_bound(u.begin(), u.end(), b[i]);
+        I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
+        const size_t Ni = ub - lb;
+        if (prob[i] == 0)
+            assert(Ni == 0);
+        else
         {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v < d.max());
-            u.push_back(v);
-        }
-        std::vector<double> prob(std::begin(p), std::end(p));
-        double s = std::accumulate(prob.begin(), prob.end(), 0.0);
-        for (int i = 0; i < prob.size(); ++i)
-            prob[i] /= s;
-        std::sort(u.begin(), u.end());
-        for (int i = 0; i < Np; ++i)
-        {
-            typedef std::vector<D::result_type>::iterator I;
-            I lb = std::lower_bound(u.begin(), u.end(), b[i]);
-            I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
-            const size_t Ni = ub - lb;
-            if (prob[i] == 0)
-                assert(Ni == 0);
-            else
+            assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
+            double mean = std::accumulate(lb, ub, 0.0) / Ni;
+            double var = 0;
+            double skew = 0;
+            double kurtosis = 0;
+            for (I j = lb; j != ub; ++j)
             {
-                assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
-                double mean = std::accumulate(lb, ub, 0.0) / Ni;
-                double var = 0;
-                double skew = 0;
-                double kurtosis = 0;
-                for (I j = lb; j != ub; ++j)
-                {
-                    double d = (*j - mean);
-                    double d2 = sqr(d);
-                    var += d2;
-                    skew += d * d2;
-                    kurtosis += d2 * d2;
-                }
-                var /= Ni;
-                double dev = std::sqrt(var);
-                skew /= Ni * dev * var;
-                kurtosis /= Ni * var * var;
-                kurtosis -= 3;
-                double x_mean = (b[i+1] + b[i]) / 2;
-                double x_var = sqr(b[i+1] - b[i]) / 12;
-                double x_skew = 0;
-                double x_kurtosis = -6./5;
-                assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-                assert(std::abs((var - x_var) / x_var) < 0.01);
-                assert(std::abs(skew - x_skew) < 0.01);
-                assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+                double dbl = (*j - mean);
+                double d2 = sqr(dbl);
+                var += d2;
+                skew += dbl * d2;
+                kurtosis += d2 * d2;
             }
+            var /= Ni;
+            double dev = std::sqrt(var);
+            skew /= Ni * dev * var;
+            kurtosis /= Ni * var * var;
+            kurtosis -= 3;
+            double x_mean = (b[i+1] + b[i]) / 2;
+            double x_var = sqr(b[i+1] - b[i]) / 12;
+            double x_skew = 0;
+            double x_kurtosis = -6./5;
+            assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+            assert(std::abs((var - x_var) / x_var) < 0.01);
+            assert(std::abs(skew - x_skew) < 0.01);
+            assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
         }
     }
+}
+
+void
+test9()
+{
+    typedef std::piecewise_constant_distribution<> D;
+    typedef std::mt19937_64 G;
+    G g;
+    double b[] = {10, 14, 16};
+    double p[] = {0, 25};
+    const size_t Np = sizeof(p) / sizeof(p[0]);
+    D d(b, b+Np+1, p);
+    const int N = 100000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::piecewise_constant_distribution<> D;
-        typedef std::mt19937_64 G;
-        G g;
-        double b[] = {10, 14, 16};
-        double p[] = {0, 25};
-        const size_t Np = sizeof(p) / sizeof(p[0]);
-        D d(b, b+Np+1, p);
-        const int N = 100000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v < d.max());
-            u.push_back(v);
-        }
-        std::vector<double> prob(std::begin(p), std::end(p));
-        double s = std::accumulate(prob.begin(), prob.end(), 0.0);
-        for (int i = 0; i < prob.size(); ++i)
-            prob[i] /= s;
-        std::sort(u.begin(), u.end());
-        for (int i = 0; i < Np; ++i)
+        D::result_type v = d(g);
+        assert(d.min() <= v && v < d.max());
+        u.push_back(v);
+    }
+    std::vector<double> prob(std::begin(p), std::end(p));
+    double s = std::accumulate(prob.begin(), prob.end(), 0.0);
+    for (int i = 0; i < prob.size(); ++i)
+        prob[i] /= s;
+    std::sort(u.begin(), u.end());
+    for (int i = 0; i < Np; ++i)
+    {
+        typedef std::vector<D::result_type>::iterator I;
+        I lb = std::lower_bound(u.begin(), u.end(), b[i]);
+        I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
+        const size_t Ni = ub - lb;
+        if (prob[i] == 0)
+            assert(Ni == 0);
+        else
         {
-            typedef std::vector<D::result_type>::iterator I;
-            I lb = std::lower_bound(u.begin(), u.end(), b[i]);
-            I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
-            const size_t Ni = ub - lb;
-            if (prob[i] == 0)
-                assert(Ni == 0);
-            else
+            assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
+            double mean = std::accumulate(lb, ub, 0.0) / Ni;
+            double var = 0;
+            double skew = 0;
+            double kurtosis = 0;
+            for (I j = lb; j != ub; ++j)
             {
-                assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
-                double mean = std::accumulate(lb, ub, 0.0) / Ni;
-                double var = 0;
-                double skew = 0;
-                double kurtosis = 0;
-                for (I j = lb; j != ub; ++j)
-                {
-                    double d = (*j - mean);
-                    double d2 = sqr(d);
-                    var += d2;
-                    skew += d * d2;
-                    kurtosis += d2 * d2;
-                }
-                var /= Ni;
-                double dev = std::sqrt(var);
-                skew /= Ni * dev * var;
-                kurtosis /= Ni * var * var;
-                kurtosis -= 3;
-                double x_mean = (b[i+1] + b[i]) / 2;
-                double x_var = sqr(b[i+1] - b[i]) / 12;
-                double x_skew = 0;
-                double x_kurtosis = -6./5;
-                assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-                assert(std::abs((var - x_var) / x_var) < 0.01);
-                assert(std::abs(skew - x_skew) < 0.01);
-                assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+                double dbl = (*j - mean);
+                double d2 = sqr(dbl);
+                var += d2;
+                skew += dbl * d2;
+                kurtosis += d2 * d2;
             }
+            var /= Ni;
+            double dev = std::sqrt(var);
+            skew /= Ni * dev * var;
+            kurtosis /= Ni * var * var;
+            kurtosis -= 3;
+            double x_mean = (b[i+1] + b[i]) / 2;
+            double x_var = sqr(b[i+1] - b[i]) / 12;
+            double x_skew = 0;
+            double x_kurtosis = -6./5;
+            assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+            assert(std::abs((var - x_var) / x_var) < 0.01);
+            assert(std::abs(skew - x_skew) < 0.01);
+            assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
         }
     }
+}
+
+void
+test10()
+{
+    typedef std::piecewise_constant_distribution<> D;
+    typedef std::mt19937_64 G;
+    G g;
+    double b[] = {10, 14, 16};
+    double p[] = {1, 0};
+    const size_t Np = sizeof(p) / sizeof(p[0]);
+    D d(b, b+Np+1, p);
+    const int N = 100000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::piecewise_constant_distribution<> D;
-        typedef std::mt19937_64 G;
-        G g;
-        double b[] = {10, 14, 16};
-        double p[] = {1, 0};
-        const size_t Np = sizeof(p) / sizeof(p[0]);
-        D d(b, b+Np+1, p);
-        const int N = 100000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v < d.max());
-            u.push_back(v);
-        }
-        std::vector<double> prob(std::begin(p), std::end(p));
-        double s = std::accumulate(prob.begin(), prob.end(), 0.0);
-        for (int i = 0; i < prob.size(); ++i)
-            prob[i] /= s;
-        std::sort(u.begin(), u.end());
-        for (int i = 0; i < Np; ++i)
+        D::result_type v = d(g);
+        assert(d.min() <= v && v < d.max());
+        u.push_back(v);
+    }
+    std::vector<double> prob(std::begin(p), std::end(p));
+    double s = std::accumulate(prob.begin(), prob.end(), 0.0);
+    for (int i = 0; i < prob.size(); ++i)
+        prob[i] /= s;
+    std::sort(u.begin(), u.end());
+    for (int i = 0; i < Np; ++i)
+    {
+        typedef std::vector<D::result_type>::iterator I;
+        I lb = std::lower_bound(u.begin(), u.end(), b[i]);
+        I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
+        const size_t Ni = ub - lb;
+        if (prob[i] == 0)
+            assert(Ni == 0);
+        else
         {
-            typedef std::vector<D::result_type>::iterator I;
-            I lb = std::lower_bound(u.begin(), u.end(), b[i]);
-            I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
-            const size_t Ni = ub - lb;
-            if (prob[i] == 0)
-                assert(Ni == 0);
-            else
+            assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
+            double mean = std::accumulate(lb, ub, 0.0) / Ni;
+            double var = 0;
+            double skew = 0;
+            double kurtosis = 0;
+            for (I j = lb; j != ub; ++j)
             {
-                assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
-                double mean = std::accumulate(lb, ub, 0.0) / Ni;
-                double var = 0;
-                double skew = 0;
-                double kurtosis = 0;
-                for (I j = lb; j != ub; ++j)
-                {
-                    double d = (*j - mean);
-                    double d2 = sqr(d);
-                    var += d2;
-                    skew += d * d2;
-                    kurtosis += d2 * d2;
-                }
-                var /= Ni;
-                double dev = std::sqrt(var);
-                skew /= Ni * dev * var;
-                kurtosis /= Ni * var * var;
-                kurtosis -= 3;
-                double x_mean = (b[i+1] + b[i]) / 2;
-                double x_var = sqr(b[i+1] - b[i]) / 12;
-                double x_skew = 0;
-                double x_kurtosis = -6./5;
-                assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-                assert(std::abs((var - x_var) / x_var) < 0.01);
-                assert(std::abs(skew - x_skew) < 0.01);
-                assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+                double dbl = (*j - mean);
+                double d2 = sqr(dbl);
+                var += d2;
+                skew += dbl * d2;
+                kurtosis += d2 * d2;
             }
+            var /= Ni;
+            double dev = std::sqrt(var);
+            skew /= Ni * dev * var;
+            kurtosis /= Ni * var * var;
+            kurtosis -= 3;
+            double x_mean = (b[i+1] + b[i]) / 2;
+            double x_var = sqr(b[i+1] - b[i]) / 12;
+            double x_skew = 0;
+            double x_kurtosis = -6./5;
+            assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+            assert(std::abs((var - x_var) / x_var) < 0.01);
+            assert(std::abs(skew - x_skew) < 0.01);
+            assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
         }
     }
+}
+
+void
+test11()
+{
+    typedef std::piecewise_constant_distribution<> D;
+    typedef std::mt19937_64 G;
+    G g;
+    double b[] = {10, 14};
+    double p[] = {1};
+    const size_t Np = sizeof(p) / sizeof(p[0]);
+    D d(b, b+Np+1, p);
+    const int N = 100000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::piecewise_constant_distribution<> D;
-        typedef std::mt19937_64 G;
-        G g;
-        double b[] = {10, 14};
-        double p[] = {1};
-        const size_t Np = sizeof(p) / sizeof(p[0]);
-        D d(b, b+Np+1, p);
-        const int N = 100000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v < d.max());
-            u.push_back(v);
-        }
-        std::vector<double> prob(std::begin(p), std::end(p));
-        double s = std::accumulate(prob.begin(), prob.end(), 0.0);
-        for (int i = 0; i < prob.size(); ++i)
-            prob[i] /= s;
-        std::sort(u.begin(), u.end());
-        for (int i = 0; i < Np; ++i)
+        D::result_type v = d(g);
+        assert(d.min() <= v && v < d.max());
+        u.push_back(v);
+    }
+    std::vector<double> prob(std::begin(p), std::end(p));
+    double s = std::accumulate(prob.begin(), prob.end(), 0.0);
+    for (int i = 0; i < prob.size(); ++i)
+        prob[i] /= s;
+    std::sort(u.begin(), u.end());
+    for (int i = 0; i < Np; ++i)
+    {
+        typedef std::vector<D::result_type>::iterator I;
+        I lb = std::lower_bound(u.begin(), u.end(), b[i]);
+        I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
+        const size_t Ni = ub - lb;
+        if (prob[i] == 0)
+            assert(Ni == 0);
+        else
         {
-            typedef std::vector<D::result_type>::iterator I;
-            I lb = std::lower_bound(u.begin(), u.end(), b[i]);
-            I ub = std::lower_bound(u.begin(), u.end(), b[i+1]);
-            const size_t Ni = ub - lb;
-            if (prob[i] == 0)
-                assert(Ni == 0);
-            else
+            assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
+            double mean = std::accumulate(lb, ub, 0.0) / Ni;
+            double var = 0;
+            double skew = 0;
+            double kurtosis = 0;
+            for (I j = lb; j != ub; ++j)
             {
-                assert(std::abs((double)Ni/N - prob[i]) / prob[i] < .01);
-                double mean = std::accumulate(lb, ub, 0.0) / Ni;
-                double var = 0;
-                double skew = 0;
-                double kurtosis = 0;
-                for (I j = lb; j != ub; ++j)
-                {
-                    double d = (*j - mean);
-                    double d2 = sqr(d);
-                    var += d2;
-                    skew += d * d2;
-                    kurtosis += d2 * d2;
-                }
-                var /= Ni;
-                double dev = std::sqrt(var);
-                skew /= Ni * dev * var;
-                kurtosis /= Ni * var * var;
-                kurtosis -= 3;
-                double x_mean = (b[i+1] + b[i]) / 2;
-                double x_var = sqr(b[i+1] - b[i]) / 12;
-                double x_skew = 0;
-                double x_kurtosis = -6./5;
-                assert(std::abs((mean - x_mean) / x_mean) < 0.01);
-                assert(std::abs((var - x_var) / x_var) < 0.01);
-                assert(std::abs(skew - x_skew) < 0.01);
-                assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
+                double dbl = (*j - mean);
+                double d2 = sqr(dbl);
+                var += d2;
+                skew += dbl * d2;
+                kurtosis += d2 * d2;
             }
+            var /= Ni;
+            double dev = std::sqrt(var);
+            skew /= Ni * dev * var;
+            kurtosis /= Ni * var * var;
+            kurtosis -= 3;
+            double x_mean = (b[i+1] + b[i]) / 2;
+            double x_var = sqr(b[i+1] - b[i]) / 12;
+            double x_skew = 0;
+            double x_kurtosis = -6./5;
+            assert(std::abs((mean - x_mean) / x_mean) < 0.01);
+            assert(std::abs((var - x_var) / x_var) < 0.01);
+            assert(std::abs(skew - x_skew) < 0.01);
+            assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
         }
     }
 }
+
+int main()
+{
+    test1();
+    test2();
+    test3();
+    test4();
+    test5();
+    test6();
+    test7();
+    test8();
+    test9();
+    test10();
+    test11();
+}
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval_param.pass.cpp
index 6850115875bb..ffd53c05d37e 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval_param.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval_param.pass.cpp
@@ -17,6 +17,7 @@
 // template<class _URNG> result_type operator()(_URNG& g, const param_type& parm);
 
 #include <random>
+#include <algorithm>
 #include <vector>
 #include <iterator>
 #include <numeric>
@@ -72,10 +73,10 @@ int main()
                 double kurtosis = 0;
                 for (I j = lb; j != ub; ++j)
                 {
-                    double d = (*j - mean);
-                    double d2 = sqr(d);
+                    double dbl = (*j - mean);
+                    double d2 = sqr(dbl);
                     var += d2;
-                    skew += d * d2;
+                    skew += dbl * d2;
                     kurtosis += d2 * d2;
                 }
                 var /= Ni;
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.plinear/eval.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.plinear/eval.pass.cpp
index af75fce512e4..03da9b8960e4 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.plinear/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.plinear/eval.pass.cpp
@@ -19,10 +19,12 @@
 #include <iostream>
 
 #include <random>
+#include <algorithm>
 #include <vector>
 #include <iterator>
 #include <numeric>
 #include <cassert>
+#include <limits>
 
 template <class T>
 inline
@@ -38,306 +40,333 @@ f(double x, double a, double m, double b, double c)
     return a + m*(sqr(x) - sqr(b))/2 + c*(x-b);
 }
 
-int main()
+void
+test1()
 {
+    typedef std::piecewise_linear_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937_64 G;
+    G g;
+    double b[] = {10, 14, 16, 17};
+    double p[] = {0, 1, 1, 0};
+    const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
+    D d(b, b+Np+1, p);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::piecewise_linear_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937_64 G;
-        G g;
-        double b[] = {10, 14, 16, 17};
-        double p[] = {0, 1, 1, 0};
-        const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
-        D d(b, b+Np+1, p);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v < d.max());
-            u.push_back(v);
-        }
-        std::sort(u.begin(), u.end());
-        int kp = -1;
-        double a;
-        double m;
-        double bk;
-        double c;
-        std::vector<double> areas(Np);
-        double S = 0;
-        for (int i = 0; i < areas.size(); ++i)
-        {
-            areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
-            S += areas[i];
-        }
-        for (int i = 0; i < areas.size(); ++i)
-            areas[i] /= S;
-        for (int i = 0; i < Np+1; ++i)
-            p[i] /= S;
-        for (int i = 0; i < N; ++i)
-        {
-            int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
-            if (k != kp)
-            {
-                a = 0;
-                for (int j = 0; j < k; ++j)
-                    a += areas[j];
-                m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
-                bk = b[k];
-                c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
-                kp = k;
-            }
-            assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
-        }
+        D::result_type v = d(g);
+        assert(d.min() <= v && v < d.max());
+        u.push_back(v);
     }
+    std::sort(u.begin(), u.end());
+    int kp = -1;
+    double a = std::numeric_limits<double>::quiet_NaN();
+    double m = std::numeric_limits<double>::quiet_NaN();
+    double bk = std::numeric_limits<double>::quiet_NaN();
+    double c = std::numeric_limits<double>::quiet_NaN();
+    std::vector<double> areas(Np);
+    double S = 0;
+    for (int i = 0; i < areas.size(); ++i)
     {
-        typedef std::piecewise_linear_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937_64 G;
-        G g;
-        double b[] = {10, 14, 16, 17};
-        double p[] = {0, 0, 1, 0};
-        const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
-        D d(b, b+Np+1, p);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v < d.max());
-            u.push_back(v);
-        }
-        std::sort(u.begin(), u.end());
-        int kp = -1;
-        double a;
-        double m;
-        double bk;
-        double c;
-        std::vector<double> areas(Np);
-        double S = 0;
-        for (int i = 0; i < areas.size(); ++i)
-        {
-            areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
-            S += areas[i];
-        }
-        for (int i = 0; i < areas.size(); ++i)
-            areas[i] /= S;
-        for (int i = 0; i < Np+1; ++i)
-            p[i] /= S;
-        for (int i = 0; i < N; ++i)
-        {
-            int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
-            if (k != kp)
-            {
-                a = 0;
-                for (int j = 0; j < k; ++j)
-                    a += areas[j];
-                m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
-                bk = b[k];
-                c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
-                kp = k;
-            }
-            assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
-        }
+        areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
+        S += areas[i];
     }
+    for (int i = 0; i < areas.size(); ++i)
+        areas[i] /= S;
+    for (int i = 0; i < Np+1; ++i)
+        p[i] /= S;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::piecewise_linear_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937_64 G;
-        G g;
-        double b[] = {10, 14, 16, 17};
-        double p[] = {1, 0, 0, 0};
-        const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
-        D d(b, b+Np+1, p);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v < d.max());
-            u.push_back(v);
-        }
-        std::sort(u.begin(), u.end());
-        int kp = -1;
-        double a;
-        double m;
-        double bk;
-        double c;
-        std::vector<double> areas(Np);
-        double S = 0;
-        for (int i = 0; i < areas.size(); ++i)
-        {
-            areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
-            S += areas[i];
-        }
-        for (int i = 0; i < areas.size(); ++i)
-            areas[i] /= S;
-        for (int i = 0; i < Np+1; ++i)
-            p[i] /= S;
-        for (int i = 0; i < N; ++i)
+        int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
+        if (k != kp)
         {
-            int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
-            if (k != kp)
-            {
-                a = 0;
-                for (int j = 0; j < k; ++j)
-                    a += areas[j];
-                m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
-                bk = b[k];
-                c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
-                kp = k;
-            }
-            assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
+            a = 0;
+            for (int j = 0; j < k; ++j)
+                a += areas[j];
+            m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
+            bk = b[k];
+            c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
+            kp = k;
         }
+        assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
     }
+}
+
+void
+test2()
+{
+    typedef std::piecewise_linear_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937_64 G;
+    G g;
+    double b[] = {10, 14, 16, 17};
+    double p[] = {0, 0, 1, 0};
+    const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
+    D d(b, b+Np+1, p);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::piecewise_linear_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937_64 G;
-        G g;
-        double b[] = {10, 14, 16};
-        double p[] = {0, 1, 0};
-        const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
-        D d(b, b+Np+1, p);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v < d.max());
-            u.push_back(v);
-        }
-        std::sort(u.begin(), u.end());
-        int kp = -1;
-        double a;
-        double m;
-        double bk;
-        double c;
-        std::vector<double> areas(Np);
-        double S = 0;
-        for (int i = 0; i < areas.size(); ++i)
-        {
-            areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
-            S += areas[i];
-        }
-        for (int i = 0; i < areas.size(); ++i)
-            areas[i] /= S;
-        for (int i = 0; i < Np+1; ++i)
-            p[i] /= S;
-        for (int i = 0; i < N; ++i)
-        {
-            int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
-            if (k != kp)
-            {
-                a = 0;
-                for (int j = 0; j < k; ++j)
-                    a += areas[j];
-                m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
-                bk = b[k];
-                c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
-                kp = k;
-            }
-            assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
-        }
+        D::result_type v = d(g);
+        assert(d.min() <= v && v < d.max());
+        u.push_back(v);
     }
+    std::sort(u.begin(), u.end());
+    int kp = -1;
+    double a = std::numeric_limits<double>::quiet_NaN();
+    double m = std::numeric_limits<double>::quiet_NaN();
+    double bk = std::numeric_limits<double>::quiet_NaN();
+    double c = std::numeric_limits<double>::quiet_NaN();
+    std::vector<double> areas(Np);
+    double S = 0;
+    for (int i = 0; i < areas.size(); ++i)
     {
-        typedef std::piecewise_linear_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937_64 G;
-        G g;
-        double b[] = {10, 14};
-        double p[] = {1, 1};
-        const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
-        D d(b, b+Np+1, p);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
-        {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v < d.max());
-            u.push_back(v);
-        }
-        std::sort(u.begin(), u.end());
-        int kp = -1;
-        double a;
-        double m;
-        double bk;
-        double c;
-        std::vector<double> areas(Np);
-        double S = 0;
-        for (int i = 0; i < areas.size(); ++i)
+        areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
+        S += areas[i];
+    }
+    for (int i = 0; i < areas.size(); ++i)
+        areas[i] /= S;
+    for (int i = 0; i < Np+1; ++i)
+        p[i] /= S;
+    for (int i = 0; i < N; ++i)
+    {
+        int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
+        if (k != kp)
         {
-            areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
-            S += areas[i];
+            a = 0;
+            for (int j = 0; j < k; ++j)
+                a += areas[j];
+            m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
+            bk = b[k];
+            c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
+            kp = k;
         }
-        for (int i = 0; i < areas.size(); ++i)
-            areas[i] /= S;
-        for (int i = 0; i < Np+1; ++i)
-            p[i] /= S;
-        for (int i = 0; i < N; ++i)
+        assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
+    }
+}
+
+void
+test3()
+{
+    typedef std::piecewise_linear_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937_64 G;
+    G g;
+    double b[] = {10, 14, 16, 17};
+    double p[] = {1, 0, 0, 0};
+    const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
+    D d(b, b+Np+1, p);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v < d.max());
+        u.push_back(v);
+    }
+    std::sort(u.begin(), u.end());
+    int kp = -1;
+    double a = std::numeric_limits<double>::quiet_NaN();
+    double m = std::numeric_limits<double>::quiet_NaN();
+    double bk = std::numeric_limits<double>::quiet_NaN();
+    double c = std::numeric_limits<double>::quiet_NaN();
+    std::vector<double> areas(Np);
+    double S = 0;
+    for (int i = 0; i < areas.size(); ++i)
+    {
+        areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
+        S += areas[i];
+    }
+    for (int i = 0; i < areas.size(); ++i)
+        areas[i] /= S;
+    for (int i = 0; i < Np+1; ++i)
+        p[i] /= S;
+    for (int i = 0; i < N; ++i)
+    {
+        int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
+        if (k != kp)
         {
-            int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
-            if (k != kp)
-            {
-                a = 0;
-                for (int j = 0; j < k; ++j)
-                    a += areas[j];
-                m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
-                bk = b[k];
-                c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
-                kp = k;
-            }
-            assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
+            a = 0;
+            for (int j = 0; j < k; ++j)
+                a += areas[j];
+            m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
+            bk = b[k];
+            c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
+            kp = k;
         }
+        assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
     }
+}
+
+void
+test4()
+{
+    typedef std::piecewise_linear_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937_64 G;
+    G g;
+    double b[] = {10, 14, 16};
+    double p[] = {0, 1, 0};
+    const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
+    D d(b, b+Np+1, p);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
     {
-        typedef std::piecewise_linear_distribution<> D;
-        typedef D::param_type P;
-        typedef std::mt19937_64 G;
-        G g;
-        double b[] = {10, 14, 16, 17};
-        double p[] = {25, 62.5, 12.5, 0};
-        const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
-        D d(b, b+Np+1, p);
-        const int N = 1000000;
-        std::vector<D::result_type> u;
-        for (int i = 0; i < N; ++i)
+        D::result_type v = d(g);
+        assert(d.min() <= v && v < d.max());
+        u.push_back(v);
+    }
+    std::sort(u.begin(), u.end());
+    int kp = -1;
+    double a = std::numeric_limits<double>::quiet_NaN();
+    double m = std::numeric_limits<double>::quiet_NaN();
+    double bk = std::numeric_limits<double>::quiet_NaN();
+    double c = std::numeric_limits<double>::quiet_NaN();
+    std::vector<double> areas(Np);
+    double S = 0;
+    for (int i = 0; i < areas.size(); ++i)
+    {
+        areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
+        S += areas[i];
+    }
+    for (int i = 0; i < areas.size(); ++i)
+        areas[i] /= S;
+    for (int i = 0; i < Np+1; ++i)
+        p[i] /= S;
+    for (int i = 0; i < N; ++i)
+    {
+        int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
+        if (k != kp)
         {
-            D::result_type v = d(g);
-            assert(d.min() <= v && v < d.max());
-            u.push_back(v);
+            a = 0;
+            for (int j = 0; j < k; ++j)
+                a += areas[j];
+            assert(k < Np);
+            m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
+            bk = b[k];
+            c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
+            kp = k;
         }
-        std::sort(u.begin(), u.end());
-        int kp = -1;
-        double a;
-        double m;
-        double bk;
-        double c;
-        std::vector<double> areas(Np);
-        double S = 0;
-        for (int i = 0; i < areas.size(); ++i)
+        assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
+    }
+}
+
+void
+test5()
+{
+    typedef std::piecewise_linear_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937_64 G;
+    G g;
+    double b[] = {10, 14};
+    double p[] = {1, 1};
+    const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
+    D d(b, b+Np+1, p);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v < d.max());
+        u.push_back(v);
+    }
+    std::sort(u.begin(), u.end());
+    int kp = -1;
+    double a = std::numeric_limits<double>::quiet_NaN();
+    double m = std::numeric_limits<double>::quiet_NaN();
+    double bk = std::numeric_limits<double>::quiet_NaN();
+    double c = std::numeric_limits<double>::quiet_NaN();
+    std::vector<double> areas(Np);
+    double S = 0;
+    for (int i = 0; i < areas.size(); ++i)
+    {
+        assert(i < Np);
+        areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
+        S += areas[i];
+    }
+    for (int i = 0; i < areas.size(); ++i)
+        areas[i] /= S;
+    for (int i = 0; i < Np+1; ++i)
+        p[i] /= S;
+    for (int i = 0; i < N; ++i)
+    {
+        int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
+        if (k != kp)
         {
-            areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
-            S += areas[i];
+            a = 0;
+            for (int j = 0; j < k; ++j)
+                a += areas[j];
+            assert(k < Np);
+            m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
+            bk = b[k];
+            c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
+            kp = k;
         }
-        for (int i = 0; i < areas.size(); ++i)
-            areas[i] /= S;
-        for (int i = 0; i < Np+1; ++i)
-            p[i] /= S;
-        for (int i = 0; i < N; ++i)
+        assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
+    }
+}
+
+void
+test6()
+{
+    typedef std::piecewise_linear_distribution<> D;
+    typedef D::param_type P;
+    typedef std::mt19937_64 G;
+    G g;
+    double b[] = {10, 14, 16, 17};
+    double p[] = {25, 62.5, 12.5, 0};
+    const size_t Np = sizeof(p) / sizeof(p[0]) - 1;
+    D d(b, b+Np+1, p);
+    const int N = 1000000;
+    std::vector<D::result_type> u;
+    for (int i = 0; i < N; ++i)
+    {
+        D::result_type v = d(g);
+        assert(d.min() <= v && v < d.max());
+        u.push_back(v);
+    }
+    std::sort(u.begin(), u.end());
+    int kp = -1;
+    double a = std::numeric_limits<double>::quiet_NaN();
+    double m = std::numeric_limits<double>::quiet_NaN();
+    double bk = std::numeric_limits<double>::quiet_NaN();
+    double c = std::numeric_limits<double>::quiet_NaN();
+    std::vector<double> areas(Np);
+    double S = 0;
+    for (int i = 0; i < areas.size(); ++i)
+    {
+        areas[i] = (p[i]+p[i+1])*(b[i+1]-b[i])/2;
+        S += areas[i];
+    }
+    for (int i = 0; i < areas.size(); ++i)
+        areas[i] /= S;
+    for (int i = 0; i < Np+1; ++i)
+        p[i] /= S;
+    for (int i = 0; i < N; ++i)
+    {
+        int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
+        if (k != kp)
         {
-            int k = std::lower_bound(b, b+Np+1, u[i]) - b - 1;
-            if (k != kp)
-            {
-                a = 0;
-                for (int j = 0; j < k; ++j)
-                    a += areas[j];
-                m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
-                bk = b[k];
-                c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
-                kp = k;
-            }
-            assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
+            a = 0;
+            for (int j = 0; j < k; ++j)
+                a += areas[j];
+            m = (p[k+1] - p[k]) / (b[k+1] - b[k]);
+            bk = b[k];
+            c = (b[k+1]*p[k] - b[k]*p[k+1]) / (b[k+1] - b[k]);
+            kp = k;
         }
+        assert(std::abs(f(u[i], a, m, bk, c) - double(i)/N) < .001);
     }
 }
+
+int main()
+{
+    test1();
+    test2();
+    test3();
+    test4();
+    test5();
+    test6();
+}
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.plinear/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.plinear/eval_param.pass.cpp
index fe704228e788..8054a69fed87 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.plinear/eval_param.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.plinear/eval_param.pass.cpp
@@ -20,7 +20,9 @@
 #include <vector>
 #include <iterator>
 #include <numeric>
+#include <algorithm>   // for sort
 #include <cassert>
+#include <limits>
 
 template <class T>
 inline
@@ -58,10 +60,10 @@ int main()
         }
         std::sort(u.begin(), u.end());
         int kp = -1;
-        double a;
-        double m;
-        double bk;
-        double c;
+        double a = std::numeric_limits<double>::quiet_NaN();
+        double m = std::numeric_limits<double>::quiet_NaN();
+        double bk = std::numeric_limits<double>::quiet_NaN();
+        double c = std::numeric_limits<double>::quiet_NaN();
         std::vector<double> areas(Np);
         double S = 0;
         for (int i = 0; i < areas.size(); ++i)
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval.pass.cpp
index 66693a8da55b..2abc9d4c6dd5 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval.pass.cpp
@@ -51,10 +51,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -92,10 +92,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -133,10 +133,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -174,10 +174,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -215,10 +215,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -256,10 +256,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -297,10 +297,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -338,10 +338,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -379,10 +379,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -431,10 +431,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval_param.pass.cpp
index d83d48cac1e3..849f25107fa8 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval_param.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval_param.pass.cpp
@@ -51,10 +51,10 @@ int main()
         double kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            double d = (u[i] - mean);
-            double d2 = sqr(d);
+            double dbl = (u[i] - mean);
+            double d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval.pass.cpp
index 2663b2683bb4..e000363f3215 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval.pass.cpp
@@ -51,10 +51,10 @@ int main()
         D::result_type kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            D::result_type d = (u[i] - mean);
-            D::result_type d2 = sqr(d);
+            D::result_type dbl = (u[i] - mean);
+            D::result_type d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -91,10 +91,10 @@ int main()
         D::result_type kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            D::result_type d = (u[i] - mean);
-            D::result_type d2 = sqr(d);
+            D::result_type dbl = (u[i] - mean);
+            D::result_type d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -131,10 +131,10 @@ int main()
         D::result_type kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            D::result_type d = (u[i] - mean);
-            D::result_type d2 = sqr(d);
+            D::result_type dbl = (u[i] - mean);
+            D::result_type d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -171,10 +171,10 @@ int main()
         D::result_type kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            D::result_type d = (u[i] - mean);
-            D::result_type d2 = sqr(d);
+            D::result_type dbl = (u[i] - mean);
+            D::result_type d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -211,10 +211,10 @@ int main()
         D::result_type kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            D::result_type d = (u[i] - mean);
-            D::result_type d2 = sqr(d);
+            D::result_type dbl = (u[i] - mean);
+            D::result_type d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -251,10 +251,10 @@ int main()
         D::result_type kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            D::result_type d = (u[i] - mean);
-            D::result_type d2 = sqr(d);
+            D::result_type dbl = (u[i] - mean);
+            D::result_type d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -291,10 +291,10 @@ int main()
         D::result_type kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            D::result_type d = (u[i] - mean);
-            D::result_type d2 = sqr(d);
+            D::result_type dbl = (u[i] - mean);
+            D::result_type d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -331,10 +331,10 @@ int main()
         D::result_type kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            D::result_type d = (u[i] - mean);
-            D::result_type d2 = sqr(d);
+            D::result_type dbl = (u[i] - mean);
+            D::result_type d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -371,10 +371,10 @@ int main()
         D::result_type kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            D::result_type d = (u[i] - mean);
-            D::result_type d2 = sqr(d);
+            D::result_type dbl = (u[i] - mean);
+            D::result_type d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -411,10 +411,10 @@ int main()
         D::result_type kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            D::result_type d = (u[i] - mean);
-            D::result_type d2 = sqr(d);
+            D::result_type dbl = (u[i] - mean);
+            D::result_type d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
@@ -451,10 +451,10 @@ int main()
         D::result_type kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            D::result_type d = (u[i] - mean);
-            D::result_type d2 = sqr(d);
+            D::result_type dbl = (u[i] - mean);
+            D::result_type d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval_param.pass.cpp
index b5803f401465..d351f0caed71 100644
--- a/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval_param.pass.cpp
+++ b/test/std/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval_param.pass.cpp
@@ -51,10 +51,10 @@ int main()
         D::result_type kurtosis = 0;
         for (int i = 0; i < u.size(); ++i)
         {
-            D::result_type d = (u[i] - mean);
-            D::result_type d2 = sqr(d);
+            D::result_type dbl = (u[i] - mean);
+            D::result_type d2 = sqr(dbl);
             var += d2;
-            skew += d * d2;
+            skew += dbl * d2;
             kurtosis += d2 * d2;
         }
         var /= u.size();
diff --git a/test/std/numerics/rand/rand.synopsis/version.pass.cpp b/test/std/numerics/rand/rand.synopsis/version.pass.cpp
deleted file mode 100644
index eae6c493e919..000000000000
--- a/test/std/numerics/rand/rand.synopsis/version.pass.cpp
+++ /dev/null
@@ -1,20 +0,0 @@
-//===----------------------------------------------------------------------===//
-//
-//                     The LLVM Compiler Infrastructure
-//
-// This file is dual licensed under the MIT and the University of Illinois Open
-// Source Licenses. See LICENSE.TXT for details.
-//
-//===----------------------------------------------------------------------===//
-
-// <random>
-
-#include <random>
-
-#ifndef _LIBCPP_VERSION
-#error _LIBCPP_VERSION not defined
-#endif
-
-int main()
-{
-}