[rand.dist.samp.pconst] plus some bug fixes in the tests of the other distributions

llvm-svn: 104224

55 files changed, 2221 insertions, 388 deletions

diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval.pass.cpp
index 6764efaa56f..d1927b2d751 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval.pass.cpp
@@ -59,10 +59,10 @@ int main()
         double x_var = d.p()*(1-d.p());
         double x_skew = (1 - 2 * d.p())/std::sqrt(x_var);
         double x_kurtosis = (6 * sqr(d.p()) - 6 * d.p() + 1)/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);
+        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);
     }
     {
         typedef std::bernoulli_distribution D;
@@ -95,9 +95,9 @@ int main()
         double x_var = d.p()*(1-d.p());
         double x_skew = (1 - 2 * d.p())/std::sqrt(x_var);
         double x_kurtosis = (6 * sqr(d.p()) - 6 * d.p() + 1)/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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval_param.pass.cpp
index bb4be855243..5754a8dc6d6 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval_param.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval_param.pass.cpp
@@ -61,10 +61,10 @@ int main()
         double x_var = p.p()*(1-p.p());
         double x_skew = (1 - 2 * p.p())/std::sqrt(x_var);
         double x_kurtosis = (6 * sqr(p.p()) - 6 * p.p() + 1)/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);
+        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);
     }
     {
         typedef std::bernoulli_distribution D;
@@ -99,9 +99,9 @@ int main()
         double x_var = p.p()*(1-p.p());
         double x_skew = (1 - 2 * p.p())/std::sqrt(x_var);
         double x_kurtosis = (6 * sqr(p.p()) - 6 * p.p() + 1)/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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval.pass.cpp
index 71bbf198b5e..a919c9dedae 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval.pass.cpp
@@ -31,10 +31,10 @@ int main()
 {
     {
         typedef std::binomial_distribution<> D;
-        typedef std::minstd_rand G;
+        typedef std::mt19937_64 G;
         G g;
         D d(5, .75);
-        const int N = 100000;
+        const int N = 1000000;
         std::vector<D::result_type> u;
         for (int i = 0; i < N; ++i)
         {
@@ -64,10 +64,10 @@ int main()
         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);
+        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);
     }
     {
         typedef std::binomial_distribution<> D;
@@ -104,10 +104,10 @@ int main()
         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);
+        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);
     }
     {
         typedef std::binomial_distribution<> D;
@@ -144,10 +144,10 @@ int main()
         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 < 0.01);
+        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);
     }
     {
         typedef std::binomial_distribution<> D;
@@ -260,10 +260,10 @@ int main()
         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((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);
+        assert(std::abs(kurtosis - x_kurtosis) < 0.01);
     }
     {
         typedef std::binomial_distribution<> D;
@@ -300,10 +300,10 @@ int main()
         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((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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::binomial_distribution<> D;
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval_param.pass.cpp
index 2632ab5f3ae..264a4a2f11e 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval_param.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bin/eval_param.pass.cpp
@@ -32,11 +32,11 @@ int main()
     {
         typedef std::binomial_distribution<> D;
         typedef D::param_type P;
-        typedef std::minstd_rand G;
+        typedef std::mt19937_64 G;
         G g;
         D d(16, .75);
         P p(5, .75);
-        const int N = 100000;
+        const int N = 1000000;
         std::vector<D::result_type> u;
         for (int i = 0; i < N; ++i)
         {
@@ -66,10 +66,10 @@ int main()
         double x_var = x_mean*(1-p.p());
         double x_skew = (1-2*p.p()) / std::sqrt(x_var);
         double x_kurtosis = (1-6*p.p()*(1-p.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);
+        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);
     }
     {
         typedef std::binomial_distribution<> D;
@@ -108,10 +108,10 @@ int main()
         double x_var = x_mean*(1-p.p());
         double x_skew = (1-2*p.p()) / std::sqrt(x_var);
         double x_kurtosis = (1-6*p.p()*(1-p.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);
+        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);
     }
     {
         typedef std::binomial_distribution<> D;
@@ -120,7 +120,7 @@ int main()
         G g;
         D d(16, .75);
         P p(40, .25);
-        const int N = 100000;
+        const int N = 1000000;
         std::vector<D::result_type> u;
         for (int i = 0; i < N; ++i)
         {
@@ -150,9 +150,9 @@ int main()
         double x_var = x_mean*(1-p.p());
         double x_skew = (1-2*p.p()) / std::sqrt(x_var);
         double x_kurtosis = (1-6*p.p()*(1-p.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 < 0.01);
+        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) < 0.3);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval.pass.cpp
index 48a6c57aac8..452bb8224c3 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval.pass.cpp
@@ -64,10 +64,10 @@ int main()
         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);
+        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);
     }
     {
         typedef std::geometric_distribution<> D;
@@ -104,10 +104,10 @@ int main()
         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);
+        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);
     }
     {
         typedef std::geometric_distribution<> D;
@@ -144,10 +144,10 @@ int main()
         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);
+        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);
     }
     {
         typedef std::geometric_distribution<> D;
@@ -184,10 +184,10 @@ int main()
         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);
+        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);
     }
     {
         typedef std::geometric_distribution<> D;
@@ -224,10 +224,10 @@ int main()
         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);
+        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);
     }
     {
         typedef std::geometric_distribution<> D;
@@ -264,9 +264,9 @@ int main()
         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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp
index bea0159faa7..184124df8ce 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp
@@ -66,10 +66,10 @@ int main()
         double x_var = x_mean / p.p();
         double x_skew = (2 - p.p()) / std::sqrt((1 - p.p()));
         double x_kurtosis = 6 + sqr(p.p()) / (1 - p.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);
+        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);
     }
     {
         typedef std::geometric_distribution<> D;
@@ -108,10 +108,10 @@ int main()
         double x_var = x_mean / p.p();
         double x_skew = (2 - p.p()) / std::sqrt((1 - p.p()));
         double x_kurtosis = 6 + sqr(p.p()) / (1 - p.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);
+        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);
     }
     {
         typedef std::geometric_distribution<> D;
@@ -150,9 +150,9 @@ int main()
         double x_var = x_mean / p.p();
         double x_skew = (2 - p.p()) / std::sqrt((1 - p.p()));
         double x_kurtosis = 6 + sqr(p.p()) / (1 - p.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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval.pass.cpp
index 96b4c180261..6bf3d3788ef 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval.pass.cpp
@@ -64,10 +64,10 @@ int main()
         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);
+        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);
     }
     {
         typedef std::negative_binomial_distribution<> D;
@@ -104,10 +104,10 @@ int main()
         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);
+        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);
     }
     {
         typedef std::negative_binomial_distribution<> D;
@@ -144,10 +144,10 @@ int main()
         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);
+        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);
     }
     {
         typedef std::negative_binomial_distribution<> D;
@@ -222,10 +222,10 @@ int main()
         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);
+        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);
     }
     {
         typedef std::negative_binomial_distribution<> D;
@@ -262,9 +262,9 @@ int main()
         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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval_param.pass.cpp
index b8906721e61..eec909ec7b8 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval_param.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.negbin/eval_param.pass.cpp
@@ -66,10 +66,10 @@ int main()
         double x_var = x_mean / p.p();
         double x_skew = (2 - p.p()) / std::sqrt(p.k() * (1 - p.p()));
         double x_kurtosis = 6. / p.k() + sqr(p.p()) / (p.k() * (1 - p.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);
+        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);
     }
     {
         typedef std::negative_binomial_distribution<> D;
@@ -108,10 +108,10 @@ int main()
         double x_var = x_mean / p.p();
         double x_skew = (2 - p.p()) / std::sqrt(p.k() * (1 - p.p()));
         double x_kurtosis = 6. / p.k() + sqr(p.p()) / (p.k() * (1 - p.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);
+        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);
     }
     {
         typedef std::negative_binomial_distribution<> D;
@@ -150,9 +150,9 @@ int main()
         double x_var = x_mean / p.p();
         double x_skew = (2 - p.p()) / std::sqrt(p.k() * (1 - p.p()));
         double x_kurtosis = 6. / p.k() + sqr(p.p()) / (p.k() * (1 - p.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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval.pass.cpp
index 5713643291c..6e9d11e87f3 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval.pass.cpp
@@ -64,10 +64,10 @@ int main()
         double x_var = 2 * d.n();
         double x_skew = std::sqrt(8 / d.n());
         double x_kurtosis = 12 / d.n();
-        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);
+        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);
     }
     {
         typedef std::chi_squared_distribution<> D;
@@ -104,10 +104,10 @@ int main()
         double x_var = 2 * d.n();
         double x_skew = std::sqrt(8 / d.n());
         double x_kurtosis = 12 / d.n();
-        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);
+        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);
     }
     {
         typedef std::chi_squared_distribution<> D;
@@ -144,9 +144,9 @@ int main()
         double x_var = 2 * d.n();
         double x_skew = std::sqrt(8 / d.n());
         double x_kurtosis = 12 / d.n();
-        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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval_param.pass.cpp
index 561f94dafda..8c456e9b1d0 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval_param.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.chisq/eval_param.pass.cpp
@@ -65,10 +65,10 @@ int main()
         double x_var = 2 * p.n();
         double x_skew = std::sqrt(8 / p.n());
         double x_kurtosis = 12 / p.n();
-        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);
+        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);
     }
     {
         typedef std::chi_squared_distribution<> D;
@@ -106,10 +106,10 @@ int main()
         double x_var = 2 * p.n();
         double x_skew = std::sqrt(8 / p.n());
         double x_kurtosis = 12 / p.n();
-        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);
+        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);
     }
     {
         typedef std::chi_squared_distribution<> D;
@@ -147,9 +147,9 @@ int main()
         double x_var = 2 * p.n();
         double x_skew = std::sqrt(8 / p.n());
         double x_kurtosis = 12 / p.n();
-        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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval.pass.cpp
index 4779eb6ca0a..6402fed534c 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval.pass.cpp
@@ -66,10 +66,10 @@ int main()
               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);
+        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);
     }
     {
         typedef std::lognormal_distribution<> D;
@@ -108,10 +108,10 @@ int main()
               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);
+        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);
     }
     {
         typedef std::lognormal_distribution<> D;
@@ -150,10 +150,10 @@ int main()
               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);
+        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);
     }
     {
         typedef std::lognormal_distribution<> D;
@@ -192,10 +192,10 @@ int main()
               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);
+        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);
     }
     {
         typedef std::lognormal_distribution<> D;
@@ -234,9 +234,9 @@ int main()
               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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval_param.pass.cpp
index 27909b4f567..f223d89718f 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval_param.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.lognormal/eval_param.pass.cpp
@@ -68,10 +68,10 @@ int main()
               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);
+        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);
     }
     {
         typedef std::lognormal_distribution<> D;
@@ -111,10 +111,10 @@ int main()
               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);
+        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);
     }
     {
         typedef std::lognormal_distribution<> D;
@@ -154,10 +154,10 @@ int main()
               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);
+        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);
     }
     {
         typedef std::lognormal_distribution<> D;
@@ -197,10 +197,10 @@ int main()
               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);
+        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);
     }
     {
         typedef std::lognormal_distribution<> D;
@@ -240,9 +240,9 @@ int main()
               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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval.pass.cpp
index abfb8aaa6b2..cc56780fdee 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval.pass.cpp
@@ -60,8 +60,8 @@ int main()
         double x_var = sqr(d.stddev());
         double x_skew = 0;
         double x_kurtosis = 0;
-        assert(std::abs(mean - x_mean) / x_mean < 0.01);
-        assert(std::abs(var - x_var) / x_var < 0.01);
+        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);
     }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval_param.pass.cpp
index e55c75fe29c..8a3dabb24a5 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval_param.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.normal/eval_param.pass.cpp
@@ -61,8 +61,8 @@ int main()
         double x_var = sqr(p.stddev());
         double x_skew = 0;
         double x_kurtosis = 0;
-        assert(std::abs(mean - x_mean) / x_mean < 0.01);
-        assert(std::abs(var - x_var) / x_var < 0.01);
+        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);
     }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval.pass.cpp
index 86ffd793384..a0bc1d807a4 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval.pass.cpp
@@ -61,9 +61,9 @@ int main()
         double x_skew = 0;
         double x_kurtosis = 6 / (d.n() - 4);
         assert(std::abs(mean - x_mean) < 0.01);
-        assert(std::abs(var - x_var) / x_var < 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 < 0.2);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.2);
     }
     {
         typedef std::student_t_distribution<> D;
@@ -97,9 +97,9 @@ int main()
         double x_skew = 0;
         double x_kurtosis = 6 / (d.n() - 4);
         assert(std::abs(mean - x_mean) < 0.01);
-        assert(std::abs(var - x_var) / x_var < 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 < 0.04);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.04);
     }
     {
         typedef std::student_t_distribution<> D;
@@ -133,8 +133,8 @@ int main()
         double x_skew = 0;
         double x_kurtosis = 6 / (d.n() - 4);
         assert(std::abs(mean - x_mean) < 0.01);
-        assert(std::abs(var - x_var) / x_var < 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 < 0.02);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval_param.pass.cpp
index 18207701a3a..3c94bfc89c4 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval_param.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.norm/rand.dist.norm.t/eval_param.pass.cpp
@@ -62,9 +62,9 @@ int main()
         double x_skew = 0;
         double x_kurtosis = 6 / (p.n() - 4);
         assert(std::abs(mean - x_mean) < 0.01);
-        assert(std::abs(var - x_var) / x_var < 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 < 0.2);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.2);
     }
     {
         typedef std::student_t_distribution<> D;
@@ -99,9 +99,9 @@ int main()
         double x_skew = 0;
         double x_kurtosis = 6 / (p.n() - 4);
         assert(std::abs(mean - x_mean) < 0.01);
-        assert(std::abs(var - x_var) / x_var < 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 < 0.04);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.04);
     }
     {
         typedef std::student_t_distribution<> D;
@@ -136,8 +136,8 @@ int main()
         double x_skew = 0;
         double x_kurtosis = 6 / (p.n() - 4);
         assert(std::abs(mean - x_mean) < 0.01);
-        assert(std::abs(var - x_var) / x_var < 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 < 0.02);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval.pass.cpp
index b4e8928fba3..c94fc80f978 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval.pass.cpp
@@ -64,10 +64,10 @@ int main()
         double x_var = 1/sqr(d.lambda());
         double x_skew = 2;
         double x_kurtosis = 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 < 0.01);
+        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);
     }
     {
         typedef std::exponential_distribution<> D;
@@ -104,10 +104,10 @@ int main()
         double x_var = 1/sqr(d.lambda());
         double x_skew = 2;
         double x_kurtosis = 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 < 0.01);
+        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);
     }
     {
         typedef std::exponential_distribution<> D;
@@ -144,9 +144,9 @@ int main()
         double x_var = 1/sqr(d.lambda());
         double x_skew = 2;
         double x_kurtosis = 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 < 0.01);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval_param.pass.cpp
index e5805f1c52b..18e9ec1d38a 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval_param.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval_param.pass.cpp
@@ -65,9 +65,9 @@ int main()
         double x_var = 1/sqr(p.lambda());
         double x_skew = 2;
         double x_kurtosis = 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 < 0.01);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval.pass.cpp
index 071ea6bc60f..22de3e9a2e0 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval.pass.cpp
@@ -63,10 +63,10 @@ int main()
         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);
+        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);
     }
     {
         typedef std::extreme_value_distribution<> D;
@@ -102,10 +102,10 @@ int main()
         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);
+        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);
     }
     {
         typedef std::extreme_value_distribution<> D;
@@ -141,10 +141,10 @@ int main()
         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);
+        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);
     }
     {
         typedef std::extreme_value_distribution<> D;
@@ -180,9 +180,9 @@ int main()
         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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval_param.pass.cpp
index dd335a05900..62add972fcc 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval_param.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.extreme/eval_param.pass.cpp
@@ -64,10 +64,10 @@ int main()
         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);
+        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);
     }
     {
         typedef std::extreme_value_distribution<> D;
@@ -104,10 +104,10 @@ int main()
         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);
+        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);
     }
     {
         typedef std::extreme_value_distribution<> D;
@@ -144,10 +144,10 @@ int main()
         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);
+        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);
     }
     {
         typedef std::extreme_value_distribution<> D;
@@ -184,9 +184,9 @@ int main()
         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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval.pass.cpp
index 0d803f36f8c..d1b4960f13d 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval.pass.cpp
@@ -64,10 +64,10 @@ int main()
         double x_var = d.alpha() * sqr(d.beta());
         double x_skew = 2 / std::sqrt(d.alpha());
         double x_kurtosis = 6 / d.alpha();
-        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);
+        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);
     }
     {
         typedef std::gamma_distribution<> D;
@@ -104,10 +104,10 @@ int main()
         double x_var = d.alpha() * sqr(d.beta());
         double x_skew = 2 / std::sqrt(d.alpha());
         double x_kurtosis = 6 / d.alpha();
-        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);
+        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);
     }
     {
         typedef std::gamma_distribution<> D;
@@ -144,9 +144,9 @@ int main()
         double x_var = d.alpha() * sqr(d.beta());
         double x_skew = 2 / std::sqrt(d.alpha());
         double x_kurtosis = 6 / d.alpha();
-        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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval_param.pass.cpp
index cdb3fc5865a..244303851ac 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval_param.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.gamma/eval_param.pass.cpp
@@ -65,10 +65,10 @@ int main()
         double x_var = p.alpha() * sqr(p.beta());
         double x_skew = 2 / std::sqrt(p.alpha());
         double x_kurtosis = 6 / p.alpha();
-        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);
+        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);
     }
     {
         typedef std::gamma_distribution<> D;
@@ -106,10 +106,10 @@ int main()
         double x_var = p.alpha() * sqr(p.beta());
         double x_skew = 2 / std::sqrt(p.alpha());
         double x_kurtosis = 6 / p.alpha();
-        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);
+        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);
     }
     {
         typedef std::gamma_distribution<> D;
@@ -147,9 +147,9 @@ int main()
         double x_var = p.alpha() * sqr(p.beta());
         double x_skew = 2 / std::sqrt(p.alpha());
         double x_kurtosis = 6 / p.alpha();
-        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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval.pass.cpp
index 2bc5c2375a1..1df0444f358 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval.pass.cpp
@@ -63,10 +63,10 @@ int main()
         double x_var = d.mean();
         double x_skew = 1 / std::sqrt(x_var);
         double x_kurtosis = 1 / 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 < 0.03);
+        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);
     }
     {
         typedef std::poisson_distribution<> D;
@@ -102,10 +102,10 @@ int main()
         double x_var = d.mean();
         double x_skew = 1 / std::sqrt(x_var);
         double x_kurtosis = 1 / 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);
+        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);
     }
     {
         typedef std::poisson_distribution<> D;
@@ -141,9 +141,9 @@ int main()
         double x_var = d.mean();
         double x_skew = 1 / std::sqrt(x_var);
         double x_kurtosis = 1 / 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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval_param.pass.cpp
index ba227297c3f..97ed29b14a9 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval_param.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.poisson/eval_param.pass.cpp
@@ -65,10 +65,10 @@ int main()
         double x_var = p.mean();
         double x_skew = 1 / std::sqrt(x_var);
         double x_kurtosis = 1 / 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 < 0.03);
+        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);
     }
     {
         typedef std::poisson_distribution<> D;
@@ -106,10 +106,10 @@ int main()
         double x_var = p.mean();
         double x_skew = 1 / std::sqrt(x_var);
         double x_kurtosis = 1 / 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);
+        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);
     }
     {
         typedef std::poisson_distribution<> D;
@@ -147,9 +147,9 @@ int main()
         double x_var = p.mean();
         double x_skew = 1 / std::sqrt(x_var);
         double x_kurtosis = 1 / 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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval.pass.cpp
index 1381a43e740..b36706c5067 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval.pass.cpp
@@ -68,10 +68,10 @@ int main()
         double x_kurtosis = (sqr(sqr(d.b())) * std::tgamma(1 + 4/d.a()) -
                        4*x_skew*x_var*sqrt(x_var)*x_mean -
                        6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3;
-        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);
+        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);
     }
     {
         typedef std::weibull_distribution<> D;
@@ -112,10 +112,10 @@ int main()
         double x_kurtosis = (sqr(sqr(d.b())) * std::tgamma(1 + 4/d.a()) -
                        4*x_skew*x_var*sqrt(x_var)*x_mean -
                        6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3;
-        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);
+        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);
     }
     {
         typedef std::weibull_distribution<> D;
@@ -156,9 +156,9 @@ int main()
         double x_kurtosis = (sqr(sqr(d.b())) * std::tgamma(1 + 4/d.a()) -
                        4*x_skew*x_var*sqrt(x_var)*x_mean -
                        6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3;
-        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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval_param.pass.cpp
index 3c1076c4cda..3100f70cada 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval_param.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.weibull/eval_param.pass.cpp
@@ -69,10 +69,10 @@ int main()
         double x_kurtosis = (sqr(sqr(p.b())) * std::tgamma(1 + 4/p.a()) -
                        4*x_skew*x_var*sqrt(x_var)*x_mean -
                        6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3;
-        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);
+        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);
     }
     {
         typedef std::weibull_distribution<> D;
@@ -114,10 +114,10 @@ int main()
         double x_kurtosis = (sqr(sqr(p.b())) * std::tgamma(1 + 4/p.a()) -
                        4*x_skew*x_var*sqrt(x_var)*x_mean -
                        6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3;
-        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);
+        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);
     }
     {
         typedef std::weibull_distribution<> D;
@@ -159,9 +159,9 @@ int main()
         double x_kurtosis = (sqr(sqr(p.b())) * std::tgamma(1 + 4/p.a()) -
                        4*x_skew*x_var*sqrt(x_var)*x_mean -
                        6*sqr(x_mean)*x_var - sqr(sqr(x_mean))) / sqr(x_var) - 3;
-        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);
+        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);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/assign.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/assign.pass.cpp
new file mode 100644
index 00000000000..c0eea1d53f9
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/assign.pass.cpp
@@ -0,0 +1,36 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// piecewise_constant_distribution& operator=(const piecewise_constant_distribution&);
+
+#include <random>
+#include <cassert>
+
+void
+test1()
+{
+    typedef std::piecewise_constant_distribution<> D;
+    double p[] = {2, 4, 1, 8};
+    double b[] = {2, 4, 5, 8, 9};
+    D d1(b, b+5, p);
+    D d2;
+    assert(d1 != d2);
+    d2 = d1;
+    assert(d1 == d2);
+}
+
+int main()
+{
+    test1();
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/copy.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/copy.pass.cpp
new file mode 100644
index 00000000000..8ba60d29b1a
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/copy.pass.cpp
@@ -0,0 +1,34 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// piecewise_constant_distribution(const piecewise_constant_distribution&);
+
+#include <random>
+#include <cassert>
+
+void
+test1()
+{
+    typedef std::piecewise_constant_distribution<> D;
+    double p[] = {2, 4, 1, 8};
+    double b[] = {2, 4, 5, 8, 9};
+    D d1(b, b+5, p);
+    D d2 = d1;
+    assert(d1 == d2);
+}
+
+int main()
+{
+    test1();
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_default.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_default.pass.cpp
new file mode 100644
index 00000000000..1706d0b2156
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_default.pass.cpp
@@ -0,0 +1,33 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// piecewise_constant_distribution(initializer_list<double> wl);
+
+#include <random>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        D d;
+        std::vector<double> iv = d.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 0);
+        assert(iv[1] == 1);
+        std::vector<double> dn = d.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 1);
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_func.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_func.pass.cpp
new file mode 100644
index 00000000000..74db04fdd56
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_func.pass.cpp
@@ -0,0 +1,64 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// template<class UnaryOperation>
+//     piecewise_constant_distribution(size_t nw, result_type xmin,
+//                                     result_type xmax, UnaryOperation fw);
+
+#include <random>
+#include <cassert>
+
+double fw(double x)
+{
+    return 2*x;
+}
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        D d(0, 0, 1, fw);
+        std::vector<double> iv = d.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 0);
+        assert(iv[1] == 1);
+        std::vector<double> dn = d.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 1);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        D d(1, 10, 12, fw);
+        std::vector<double> iv = d.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 10);
+        assert(iv[1] == 12);
+        std::vector<double> dn = d.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 0.5);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        D d(2, 6, 14, fw);
+        std::vector<double> iv = d.intervals();
+        assert(iv.size() == 3);
+        assert(iv[0] == 6);
+        assert(iv[1] == 10);
+        assert(iv[2] == 14);
+        std::vector<double> dn = d.densities();
+        assert(dn.size() == 2);
+        assert(dn[0] == 0.1);
+        assert(dn[1] == 0.15);
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_init_func.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_init_func.pass.cpp
new file mode 100644
index 00000000000..abbf559665d
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_init_func.pass.cpp
@@ -0,0 +1,78 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// piecewise_constant_distribution(initializer_list<result_type> bl,
+//                                 UnaryOperation fw);
+
+#include <iostream>
+
+#include <random>
+#include <cassert>
+
+double f(double x)
+{
+    return x*2;
+}
+
+int main()
+{
+#ifdef _LIBCPP_MOVE
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        D d({}, f);
+        std::vector<double> iv = d.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 0);
+        assert(iv[1] == 1);
+        std::vector<double> dn = d.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 1);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        D d({12}, f);
+        std::vector<double> iv = d.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 0);
+        assert(iv[1] == 1);
+        std::vector<double> dn = d.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 1);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        D d({12, 14}, f);
+        std::vector<double> iv = d.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 12);
+        assert(iv[1] == 14);
+        std::vector<double> dn = d.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 0.5);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        D d({5.5, 7.5, 11.5}, f);
+        std::vector<double> iv = d.intervals();
+        assert(iv.size() == 3);
+        assert(iv[0] == 5.5);
+        assert(iv[1] == 7.5);
+        assert(iv[2] == 11.5);
+        std::vector<double> dn = d.densities();
+        assert(dn.size() == 2);
+        assert(dn[0] == 0.203125);
+        assert(dn[1] == 0.1484375);
+    }
+#endif
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_iterator.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_iterator.pass.cpp
new file mode 100644
index 00000000000..985e147792c
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_iterator.pass.cpp
@@ -0,0 +1,96 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// template<class InputIterator>
+//     piecewise_constant_distribution(InputIteratorB firstB,
+//                                     InputIteratorB lastB,
+//                                     InputIteratorW firstW);
+
+#include <random>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        double b[] = {10};
+        double p[] = {12};
+        D d(b, b, p);
+        std::vector<double> iv = d.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 0);
+        assert(iv[1] == 1);
+        std::vector<double> dn = d.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 1);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        double b[] = {10};
+        double p[] = {12};
+        D d(b, b+1, p);
+        std::vector<double> iv = d.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 0);
+        assert(iv[1] == 1);
+        std::vector<double> dn = d.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 1);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        double b[] = {10, 15};
+        double p[] = {12};
+        D d(b, b+2, p);
+        std::vector<double> iv = d.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 10);
+        assert(iv[1] == 15);
+        std::vector<double> dn = d.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 1/5.);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        double b[] = {10, 15, 16};
+        double p[] = {.25, .75};
+        D d(b, b+3, p);
+        std::vector<double> iv = d.intervals();
+        assert(iv.size() == 3);
+        assert(iv[0] == 10);
+        assert(iv[1] == 15);
+        assert(iv[2] == 16);
+        std::vector<double> dn = d.densities();
+        assert(dn.size() == 2);
+        assert(dn[0] == .25/5.);
+        assert(dn[1] == .75);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        double b[] = {10, 14, 16, 17};
+        double p[] = {25, 62.5, 12.5};
+        D d(b, b+4, p);
+        std::vector<double> iv = d.intervals();
+        assert(iv.size() == 4);
+        assert(iv[0] == 10);
+        assert(iv[1] == 14);
+        assert(iv[2] == 16);
+        assert(iv[3] == 17);
+        std::vector<double> dn = d.densities();
+        assert(dn.size() == 3);
+        assert(dn[0] == .0625);
+        assert(dn[1] == .3125);
+        assert(dn[2] == .125);
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_param.pass.cpp
new file mode 100644
index 00000000000..7249932ce0f
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/ctor_param.pass.cpp
@@ -0,0 +1,41 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// explicit piecewise_constant_distribution(const param_type& parm);
+
+#include <random>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        double b[] = {10, 14, 16, 17};
+        double p[] = {25, 62.5, 12.5};
+        P pa(b, b+4, p);
+        D d(pa);
+        std::vector<double> iv = d.intervals();
+        assert(iv.size() == 4);
+        assert(iv[0] == 10);
+        assert(iv[1] == 14);
+        assert(iv[2] == 16);
+        assert(iv[3] == 17);
+        std::vector<double> dn = d.densities();
+        assert(dn.size() == 3);
+        assert(dn[0] == .0625);
+        assert(dn[1] == .3125);
+        assert(dn[2] == .125);
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eq.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eq.pass.cpp
new file mode 100644
index 00000000000..605a3eb3460
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eq.pass.cpp
@@ -0,0 +1,47 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// bool operator=(const piecewise_constant_distribution& x,
+//                const piecewise_constant_distribution& y);
+// bool operator!(const piecewise_constant_distribution& x,
+//                const piecewise_constant_distribution& y);
+
+#include <random>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        D d1;
+        D d2;
+        assert(d1 == d2);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        double b[] = {10, 14, 16, 17};
+        double p[] = {25, 62.5, 12.5};
+        D d1(b, b+4, p);
+        D d2(b, b+4, p);
+        assert(d1 == d2);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        double b[] = {10, 14, 16, 17};
+        double p[] = {25, 62.5, 12.5};
+        D d1(b, b+4, p);
+        D d2;
+        assert(d1 != d2);
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval.pass.cpp
new file mode 100644
index 00000000000..483526ba097
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval.pass.cpp
@@ -0,0 +1,693 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// template<class _URNG> result_type operator()(_URNG& g);
+
+#include <random>
+#include <vector>
+#include <iterator>
+#include <numeric>
+#include <cassert>
+
+template <class T>
+inline
+T
+sqr(T x)
+{
+    return x*x;
+}
+
+int main()
+{
+    {
+        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)
+        {
+            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)
+                {
+                    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);
+            }
+        }
+    }
+    {
+        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)
+        {
+            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)
+                {
+                    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);
+            }
+        }
+    }
+    {
+        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::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)
+                {
+                    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);
+            }
+        }
+    }
+    {
+        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
+            {
+                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);
+            }
+        }
+    }
+    {
+        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)
+        {
+            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)
+                {
+                    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);
+            }
+        }
+    }
+    {
+        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
+            {
+                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);
+            }
+        }
+    }
+    {
+        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)
+        {
+            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)
+                {
+                    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);
+            }
+        }
+    }
+    {
+        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::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)
+                {
+                    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);
+            }
+        }
+    }
+    {
+        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)
+        {
+            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)
+                {
+                    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);
+            }
+        }
+    }
+    {
+        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)
+        {
+            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)
+                {
+                    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);
+            }
+        }
+    }
+    {
+        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)
+        {
+            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)
+                {
+                    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);
+            }
+        }
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval_param.pass.cpp
new file mode 100644
index 00000000000..b842bed501a
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/eval_param.pass.cpp
@@ -0,0 +1,95 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// template<class _URNG> result_type operator()(_URNG& g, const param_type& parm);
+
+#include <random>
+#include <vector>
+#include <iterator>
+#include <numeric>
+#include <cassert>
+
+template <class T>
+inline
+T
+sqr(T x)
+{
+    return x*x;
+}
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_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};
+        const size_t Np = sizeof(p) / sizeof(p[0]);
+        D d;
+        P pa(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, pa);
+            assert(10 <= v && v < 17);
+            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)
+                {
+                    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);
+            }
+        }
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/get_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/get_param.pass.cpp
new file mode 100644
index 00000000000..0f60a40b52f
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/get_param.pass.cpp
@@ -0,0 +1,32 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// param_type param() const;
+
+#include <random>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        double b[] = {10, 14, 16, 17};
+        double p[] = {25, 62.5, 12.5};
+        const size_t Np = sizeof(p) / sizeof(p[0]);
+        P pa(b, b+Np+1, p);
+        D d(pa);
+        assert(d.param() == pa);
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/io.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/io.pass.cpp
new file mode 100644
index 00000000000..64f0b808229
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/io.pass.cpp
@@ -0,0 +1,44 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// template <class charT, class traits>
+// basic_ostream<charT, traits>&
+// operator<<(basic_ostream<charT, traits>& os,
+//            const piecewise_constant_distribution& x);
+// 
+// template <class charT, class traits>
+// basic_istream<charT, traits>&
+// operator>>(basic_istream<charT, traits>& is,
+//            piecewise_constant_distribution& x);
+
+#include <random>
+#include <sstream>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        double b[] = {10, 14, 16, 17};
+        double p[] = {25, 62.5, 12.5};
+        const size_t Np = sizeof(p) / sizeof(p[0]);
+        D d1(b, b+Np+1, p);
+        std::ostringstream os;
+        os << d1;
+        std::istringstream is(os.str());
+        D d2;
+        is >> d2;
+        assert(d1 == d2);
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/max.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/max.pass.cpp
new file mode 100644
index 00000000000..c1846efac42
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/max.pass.cpp
@@ -0,0 +1,30 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// result_type max() const;
+
+#include <random>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        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);
+        assert(d.max() == 17);
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/min.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/min.pass.cpp
new file mode 100644
index 00000000000..7d18ce11e5d
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/min.pass.cpp
@@ -0,0 +1,30 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// result_type min() const;
+
+#include <random>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        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);
+        assert(d.min() == 10);
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_assign.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_assign.pass.cpp
new file mode 100644
index 00000000000..55a0f65c6ce
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_assign.pass.cpp
@@ -0,0 +1,34 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+// {
+//     class param_type;
+
+#include <random>
+#include <limits>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        double b[] = {10, 14, 16, 17};
+        double p[] = {25, 62.5, 12.5};
+        const size_t Np = sizeof(p) / sizeof(p[0]);
+        P p0(b, b+Np+1, p);
+        P p1;
+        p1 = p0;
+        assert(p1 == p0);
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_copy.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_copy.pass.cpp
new file mode 100644
index 00000000000..e6f9f8d9789
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_copy.pass.cpp
@@ -0,0 +1,33 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+// {
+//     class param_type;
+
+#include <random>
+#include <limits>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        double b[] = {10, 14, 16, 17};
+        double p[] = {25, 62.5, 12.5};
+        const size_t Np = sizeof(p) / sizeof(p[0]);
+        P p0(b, b+Np+1, p);
+        P p1 = p0;
+        assert(p1 == p0);
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_default.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_default.pass.cpp
new file mode 100644
index 00000000000..63f338d2bb7
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_default.pass.cpp
@@ -0,0 +1,34 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// param_type();
+
+#include <random>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        P pa;
+        std::vector<double> iv = pa.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 0);
+        assert(iv[1] == 1);
+        std::vector<double> dn = pa.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 1);
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_func.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_func.pass.cpp
new file mode 100644
index 00000000000..b8fcfd583d4
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_func.pass.cpp
@@ -0,0 +1,67 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// template<class UnaryOperation>
+//     param_type(size_t nw, double xmin, double xmax,
+//                           UnaryOperation fw);
+
+#include <random>
+#include <cassert>
+
+double fw(double x)
+{
+    return 2*x;
+}
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        P pa(0, 0, 1, fw);
+        std::vector<double> iv = pa.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 0);
+        assert(iv[1] == 1);
+        std::vector<double> dn = pa.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 1);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        P pa(1, 10, 12, fw);
+        std::vector<double> iv = pa.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 10);
+        assert(iv[1] == 12);
+        std::vector<double> dn = pa.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 0.5);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        P pa(2, 6, 14, fw);
+        std::vector<double> iv = pa.intervals();
+        assert(iv.size() == 3);
+        assert(iv[0] == 6);
+        assert(iv[1] == 10);
+        assert(iv[2] == 14);
+        std::vector<double> dn = pa.densities();
+        assert(dn.size() == 2);
+        assert(dn[0] == 0.1);
+        assert(dn[1] == 0.15);
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_init_func.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_init_func.pass.cpp
new file mode 100644
index 00000000000..8d278364348
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_init_func.pass.cpp
@@ -0,0 +1,79 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// param_type(initializer_list<result_type> bl, UnaryOperation fw);
+
+#include <random>
+#include <cassert>
+
+double f(double x)
+{
+    return x*2;
+}
+
+int main()
+{
+#ifdef _LIBCPP_MOVE
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        P pa({}, f);
+        std::vector<double> iv = pa.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 0);
+        assert(iv[1] == 1);
+        std::vector<double> dn = pa.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 1);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        P pa({12}, f);
+        std::vector<double> iv = pa.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 0);
+        assert(iv[1] == 1);
+        std::vector<double> dn = pa.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 1);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        P pa({12, 14}, f);
+        std::vector<double> iv = pa.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 12);
+        assert(iv[1] == 14);
+        std::vector<double> dn = pa.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 0.5);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        P pa({5.5, 7.5, 11.5}, f);
+        std::vector<double> iv = pa.intervals();
+        assert(iv.size() == 3);
+        assert(iv[0] == 5.5);
+        assert(iv[1] == 7.5);
+        assert(iv[2] == 11.5);
+        std::vector<double> dn = pa.densities();
+        assert(dn.size() == 2);
+        assert(dn[0] == 0.203125);
+        assert(dn[1] == 0.1484375);
+    }
+#endif
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_iterator.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_iterator.pass.cpp
new file mode 100644
index 00000000000..ee2e12908f7
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_ctor_iterator.pass.cpp
@@ -0,0 +1,100 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// template<class InputIterator>
+//     param_type(InputIteratorB firstB, InputIteratorB lastB,
+//                InputIteratorW firstW);
+
+#include <random>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        double b[] = {10};
+        double p[] = {12};
+        P pa(b, b, p);
+        std::vector<double> iv = pa.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 0);
+        assert(iv[1] == 1);
+        std::vector<double> dn = pa.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 1);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        double b[] = {10};
+        double p[] = {12};
+        P pa(b, b+1, p);
+        std::vector<double> iv = pa.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 0);
+        assert(iv[1] == 1);
+        std::vector<double> dn = pa.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 1);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        double b[] = {10, 15};
+        double p[] = {12};
+        P pa(b, b+2, p);
+        std::vector<double> iv = pa.intervals();
+        assert(iv.size() == 2);
+        assert(iv[0] == 10);
+        assert(iv[1] == 15);
+        std::vector<double> dn = pa.densities();
+        assert(dn.size() == 1);
+        assert(dn[0] == 1/5.);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        double b[] = {10, 15, 16};
+        double p[] = {.25, .75};
+        P pa(b, b+3, p);
+        std::vector<double> iv = pa.intervals();
+        assert(iv.size() == 3);
+        assert(iv[0] == 10);
+        assert(iv[1] == 15);
+        assert(iv[2] == 16);
+        std::vector<double> dn = pa.densities();
+        assert(dn.size() == 2);
+        assert(dn[0] == .25/5.);
+        assert(dn[1] == .75);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        double b[] = {10, 14, 16, 17};
+        double p[] = {25, 62.5, 12.5};
+        P pa(b, b+4, p);
+        std::vector<double> iv = pa.intervals();
+        assert(iv.size() == 4);
+        assert(iv[0] == 10);
+        assert(iv[1] == 14);
+        assert(iv[2] == 16);
+        assert(iv[3] == 17);
+        std::vector<double> dn = pa.densities();
+        assert(dn.size() == 3);
+        assert(dn[0] == .0625);
+        assert(dn[1] == .3125);
+        assert(dn[2] == .125);
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_eq.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_eq.pass.cpp
new file mode 100644
index 00000000000..85e7232266d
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_eq.pass.cpp
@@ -0,0 +1,41 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+// {
+//     class param_type;
+
+#include <random>
+#include <limits>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        double b[] = {10, 14, 16, 17};
+        double p[] = {25, 62.5, 12.5};
+        P p1(b, b+4, p);
+        P p2(b, b+4, p);
+        assert(p1 == p2);
+    }
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        double b[] = {10, 14, 16, 17};
+        double p[] = {25, 62.5, 12.5};
+        P p1(b, b+3, p);
+        P p2(b, b+4, p);
+        assert(p1 != p2);
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_types.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_types.pass.cpp
new file mode 100644
index 00000000000..91db248af21
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/param_types.pass.cpp
@@ -0,0 +1,28 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+// {
+//     class param_type;
+
+#include <random>
+#include <type_traits>
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type param_type;
+        typedef param_type::distribution_type distribution_type;
+        static_assert((std::is_same<D, distribution_type>::value), "");
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/set_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/set_param.pass.cpp
new file mode 100644
index 00000000000..6a5fd0cfa08
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/set_param.pass.cpp
@@ -0,0 +1,32 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+
+// void param(const param_type& parm);
+
+#include <random>
+#include <cassert>
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::param_type P;
+        double b[] = {10, 14, 16, 17};
+        double p[] = {25, 62.5, 12.5};
+        P pa(b, b+4, p);
+        D d;
+        d.param(pa);
+        assert(d.param() == pa);
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/types.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/types.pass.cpp
new file mode 100644
index 00000000000..f3e21f27d51
--- /dev/null
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.samp/rand.dist.samp.pconst/types.pass.cpp
@@ -0,0 +1,32 @@
+//===----------------------------------------------------------------------===//
+//
+//                     The LLVM Compiler Infrastructure
+//
+// This file is distributed under the University of Illinois Open Source
+// License. See LICENSE.TXT for details.
+//
+//===----------------------------------------------------------------------===//
+
+// <random>
+
+// template<class RealType = double>
+// class piecewise_constant_distribution
+// {
+//     typedef bool result_type;
+
+#include <random>
+#include <type_traits>
+
+int main()
+{
+    {
+        typedef std::piecewise_constant_distribution<> D;
+        typedef D::result_type result_type;
+        static_assert((std::is_same<result_type, double>::value), "");
+    }
+    {
+        typedef std::piecewise_constant_distribution<float> D;
+        typedef D::result_type result_type;
+        static_assert((std::is_same<result_type, float>::value), "");
+    }
+}
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval.pass.cpp
index 3443e16f26f..17840983318 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval.pass.cpp
@@ -65,10 +65,10 @@ int main()
         double x_skew = 0;
         double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
                             (5. * (sqr((double)d.b() - d.a() + 1) - 1));
-        assert(std::abs(mean - x_mean) / x_mean < 0.01);
-        assert(std::abs(var - x_var) / x_var < 0.01);
+        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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_int_distribution<> D;
@@ -106,10 +106,10 @@ int main()
         double x_skew = 0;
         double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
                             (5. * (sqr((double)d.b() - d.a() + 1) - 1));
-        assert(std::abs(mean - x_mean) / x_mean < 0.01);
-        assert(std::abs(var - x_var) / x_var < 0.01);
+        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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_int_distribution<> D;
@@ -147,10 +147,10 @@ int main()
         double x_skew = 0;
         double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
                             (5. * (sqr((double)d.b() - d.a() + 1) - 1));
-        assert(std::abs(mean - x_mean) / x_mean < 0.01);
-        assert(std::abs(var - x_var) / x_var < 0.01);
+        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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_int_distribution<> D;
@@ -188,10 +188,10 @@ int main()
         double x_skew = 0;
         double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
                             (5. * (sqr((double)d.b() - d.a() + 1) - 1));
-        assert(std::abs(mean - x_mean) / x_mean < 0.01);
-        assert(std::abs(var - x_var) / x_var < 0.01);
+        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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_int_distribution<> D;
@@ -229,10 +229,10 @@ int main()
         double x_skew = 0;
         double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
                             (5. * (sqr((double)d.b() - d.a() + 1) - 1));
-        assert(std::abs(mean - x_mean) / x_mean < 0.01);
-        assert(std::abs(var - x_var) / x_var < 0.01);
+        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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_int_distribution<> D;
@@ -270,10 +270,10 @@ int main()
         double x_skew = 0;
         double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
                             (5. * (sqr((double)d.b() - d.a() + 1) - 1));
-        assert(std::abs(mean - x_mean) / x_mean < 0.01);
-        assert(std::abs(var - x_var) / x_var < 0.01);
+        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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_int_distribution<> D;
@@ -311,10 +311,10 @@ int main()
         double x_skew = 0;
         double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
                             (5. * (sqr((double)d.b() - d.a() + 1) - 1));
-        assert(std::abs(mean - x_mean) / x_mean < 0.01);
-        assert(std::abs(var - x_var) / x_var < 0.01);
+        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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_int_distribution<> D;
@@ -352,10 +352,10 @@ int main()
         double x_skew = 0;
         double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
                             (5. * (sqr((double)d.b() - d.a() + 1) - 1));
-        assert(std::abs(mean - x_mean) / x_mean < 0.01);
-        assert(std::abs(var - x_var) / x_var < 0.01);
+        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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_int_distribution<> D;
@@ -393,10 +393,10 @@ int main()
         double x_skew = 0;
         double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
                             (5. * (sqr((double)d.b() - d.a() + 1) - 1));
-        assert(std::abs(mean - x_mean) / x_mean < 0.01);
-        assert(std::abs(var - x_var) / x_var < 0.01);
+        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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_int_distribution<> D;
@@ -445,9 +445,9 @@ int main()
         double x_skew = 0;
         double x_kurtosis = -6. * (sqr((double)d.b() - d.a() + 1) + 1) /
                             (5. * (sqr((double)d.b() - d.a() + 1) - 1));
-        assert(std::abs(mean - x_mean) / x_mean < 0.01);
-        assert(std::abs(var - x_var) / x_var < 0.01);
+        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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval_param.pass.cpp
index 6bbd4fabb68..f84a6d42c94 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval_param.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.int/eval_param.pass.cpp
@@ -67,9 +67,9 @@ int main()
         double x_skew = 0;
         double x_kurtosis = -6. * (sqr((double)p.b() - p.a() + 1) + 1) /
                             (5. * (sqr((double)p.b() - p.a() + 1) - 1));
-        assert(std::abs(mean - x_mean) / x_mean < 0.01);
-        assert(std::abs(var - x_var) / x_var < 0.01);
+        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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval.pass.cpp
index b6de39535d2..a733fc915f7 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval.pass.cpp
@@ -64,10 +64,10 @@ int main()
         D::result_type x_var = sqr(d.b() - d.a()) / 12;
         D::result_type x_skew = 0;
         D::result_type 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((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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_real_distribution<> D;
@@ -104,10 +104,10 @@ int main()
         D::result_type x_var = sqr(d.b() - d.a()) / 12;
         D::result_type x_skew = 0;
         D::result_type 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((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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_real_distribution<> D;
@@ -144,10 +144,10 @@ int main()
         D::result_type x_var = sqr(d.b() - d.a()) / 12;
         D::result_type x_skew = 0;
         D::result_type 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((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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_real_distribution<> D;
@@ -184,10 +184,10 @@ int main()
         D::result_type x_var = sqr(d.b() - d.a()) / 12;
         D::result_type x_skew = 0;
         D::result_type 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((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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_real_distribution<> D;
@@ -224,10 +224,10 @@ int main()
         D::result_type x_var = sqr(d.b() - d.a()) / 12;
         D::result_type x_skew = 0;
         D::result_type 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((mean - x_mean) / x_mean) < 0.01);
+        assert(std::abs((var - x_var) / x_var) < 0.01);
         assert(std::abs(skew - x_skew) < 0.02);
-        assert(std::abs(kurtosis - x_kurtosis) / x_kurtosis < 0.01);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_real_distribution<> D;
@@ -264,10 +264,10 @@ int main()
         D::result_type x_var = sqr(d.b() - d.a()) / 12;
         D::result_type x_skew = 0;
         D::result_type 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((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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_real_distribution<> D;
@@ -304,10 +304,10 @@ int main()
         D::result_type x_var = sqr(d.b() - d.a()) / 12;
         D::result_type x_skew = 0;
         D::result_type 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((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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_real_distribution<> D;
@@ -344,10 +344,10 @@ int main()
         D::result_type x_var = sqr(d.b() - d.a()) / 12;
         D::result_type x_skew = 0;
         D::result_type 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((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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_real_distribution<> D;
@@ -384,10 +384,10 @@ int main()
         D::result_type x_var = sqr(d.b() - d.a()) / 12;
         D::result_type x_skew = 0;
         D::result_type 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((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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_real_distribution<> D;
@@ -425,9 +425,9 @@ int main()
         D::result_type x_skew = 0;
         D::result_type x_kurtosis = -6./5;
         assert(std::abs(mean - x_mean) < 0.01);
-        assert(std::abs(var - x_var) / x_var < 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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
     {
         typedef std::uniform_real_distribution<> D;
@@ -464,9 +464,9 @@ int main()
         D::result_type x_var = sqr(d.b() - d.a()) / 12;
         D::result_type x_skew = 0;
         D::result_type 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((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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval_param.pass.cpp b/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval_param.pass.cpp
index 79e2924ef62..0f726ed7a0f 100644
--- a/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval_param.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.dis/rand.dist.uni/rand.dist.uni.real/eval_param.pass.cpp
@@ -66,9 +66,9 @@ int main()
         D::result_type x_var = sqr(p.b() - p.a()) / 12;
         D::result_type x_skew = 0;
         D::result_type 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((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);
+        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
     }
 }
diff --git a/libcxx/test/numerics/rand/rand.predef/default_random_engine.pass.cpp b/libcxx/test/numerics/rand/rand.predef/default_random_engine.pass.cpp
index d936f89f602..91b0902c86d 100644
--- a/libcxx/test/numerics/rand/rand.predef/default_random_engine.pass.cpp
+++ b/libcxx/test/numerics/rand/rand.predef/default_random_engine.pass.cpp
@@ -20,5 +20,5 @@ int main()
 {
     std::default_random_engine e;
     e.discard(9999);
-    assert(e() == 1043618065u);
+    assert(e() == 399268537u);
 }