diff --git a/FastRngTests/Double/Distributions/Uniform.cs b/FastRngTests/Double/Distributions/Uniform.cs
new file mode 100644
index 0000000..0955c49
--- /dev/null
+++ b/FastRngTests/Double/Distributions/Uniform.cs
@@ -0,0 +1,81 @@
+using System;
+using System.Threading.Tasks;
+using FastRng.Double;
+using NUnit.Framework;
+
+namespace FastRngTests.Double.Distributions
+{
+    public class Uniform
+    {
+        [Test]
+        [Category(TestCategories.COVER)]
+        [Category(TestCategories.NORMAL)]
+        public async Task KolmogorovSmirnovTest()
+        {
+            // Kolmogorov-Smirnov test for distributions.
+            // See Knuth volume 2, page 48-51 (third edition).
+            // This test should *fail* on average one time in 1000 runs.
+            // That's life with random number generators: if the test passed all the time, 
+            // the source wouldn't be random enough!  If the test were to fail more frequently,
+            // the most likely explanation would be a bug in the code.
+            
+            const int NUM_ROUNDS = 10_000;
+            const double FAILURE_PROBABILITY = 0.001; // probability of test failing with normal distributed input
+            const double P_LOW = 0.25 * FAILURE_PROBABILITY;
+            const double P_HIGH = 1.0 - 0.25 * FAILURE_PROBABILITY;
+            
+            var samples = new double[NUM_ROUNDS];
+            var rng = new MultiThreadedRng();
+            int n;
+             
+            for (n = 0; n != NUM_ROUNDS; ++n)
+                samples[n] = await rng.GetUniform();
+ 
+            rng.StopProducer();
+            Array.Sort(samples);
+
+            var jMinus = 0;
+            var jPlus = 0;
+            var kPlus = -double.MaxValue;
+            var kMinus = -double.MaxValue;
+ 
+            for (n = 0; n != NUM_ROUNDS; ++n)
+            {
+                var cdf = samples[n];
+                var temp = (n + 1.0) / NUM_ROUNDS - cdf;
+                
+                if (kPlus < temp)
+                {
+                    kPlus = temp;
+                    jPlus = n;
+                }
+                
+                temp = cdf - (n + 0.0) / NUM_ROUNDS;
+                if (kMinus < temp)
+                {
+                    kMinus = temp;
+                    jMinus = n;
+                }
+            }
+ 
+            var sqrtNumReps = Math.Sqrt(NUM_ROUNDS);
+            kPlus *= sqrtNumReps;
+            kMinus *= sqrtNumReps;
+ 
+            // We divide the failure probability by four because we have four tests:
+            // left and right tests for K+ and K-.
+            var cutoffLow = Math.Sqrt(0.5 * Math.Log(1.0 / (1.0 - P_LOW))) - 1.0 / (6.0 * sqrtNumReps);
+            var cutoffHigh = Math.Sqrt(0.5 * Math.Log(1.0 / (1.0 - P_HIGH))) - 1.0 / (6.0 * sqrtNumReps);
+ 
+            TestContext.WriteLine($"K+ = {kPlus} | K- = {kMinus}");
+            TestContext.WriteLine($"K+ max at position {jPlus} = {samples[jPlus]}");
+            TestContext.WriteLine($"K- max at position {jMinus} = {samples[jMinus]}");
+            TestContext.WriteLine($"Acceptable interval: [{cutoffLow}, {cutoffHigh}]");
+
+            Assert.That(kPlus, Is.GreaterThanOrEqualTo(cutoffLow), "K+ is lower than low cutoff");
+            Assert.That(kPlus, Is.LessThanOrEqualTo(cutoffHigh), "K+ is higher than high cutoff");
+            Assert.That(kMinus, Is.GreaterThanOrEqualTo(cutoffLow), "K- is lower than low cutoff");
+            Assert.That(kMinus, Is.LessThanOrEqualTo(cutoffHigh), "K- is lower than high cutoff");
+        }
+    }
+}
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