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				@@ -878,11 +878,14 @@ test_uniform_interval(void *arg) 
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				  * is higher: 1 - Binom(0; n, alpha) = 1 - (1 - alpha)^n.  For n = 10, 
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				  * this is about 10%, and for n = 100 it is well over 50%. 
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				  * 
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				- * We can drive it down by running each test twice, and accepting it if 
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				- * it passes at least once; in that case, it is as if we used Binom(2; 
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				- * 2, alpha) = alpha^2 as the false positive rate for each test, and 
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				- * for n = 10 tests, it would be 0.1%, and for n = 100 tests, still 
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				- * only 1%. 
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				+ * Given that these tests will run with every CI job, we want to drive down the 
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				+ * false positive rate. We can drive it down by running each test four times, 
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				+ * and accepting it if it passes at least once; in that case, it is as if we 
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				+ * used Binom(4; 2, alpha) = alpha^4 as the false positive rate for each test, 
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				+ * and for n = 10 tests, it would be 9.99999959506e-08. If each CI build has 14 
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				+ * jobs, then the chance of a CI build failing is 1.39999903326e-06, which 
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				+ * means that a CI build will break with probability 50% after about 495106 
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				+ * builds. 
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				  * 
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				  * The critical value for a chi^2 distribution with 100 degrees of 
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				  * freedom and false positive rate alpha = 1% was taken from: 
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				@@ -895,7 +898,7 @@ test_uniform_interval(void *arg) 
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				 static const size_t NSAMPLES = 100000; 
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				 /* Number of chances we give to the test to succeed. */ 
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				-static const unsigned NTRIALS = 2; 
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				+static const unsigned NTRIALS = 4; 
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				 /* Number of times we want the test to pass per NTRIALS. */ 
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				 static const unsigned NPASSES_MIN = 1; 
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