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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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