4  * Use of this source code is governed by a BSD-style license that can be
18     // Min and max Anderson-Darling values allowable for k=32  in anderson_darling_test()
19     const double kADMin32 = 0.202;        // p-value of ~0.1  in anderson_darling_test()
20     const double kADMax32 = 3.89;         // p-value of ~0.99  in anderson_darling_test()
25     // and compute Anderson-Darling statistic to ensure these are uniform  in anderson_darling_test()
28         double v = p[k]*(1.0 - p[31-k]);  in anderson_darling_test()
29         if (v < 1.0e-30) {  in anderson_darling_test()
30            v = 1.0e-30;  in anderson_darling_test()
32         s += (2.0*(k+1)-1.0)*log(v);  in anderson_darling_test()
34     double a2 = -32.0 - 0.03125*s;  in anderson_darling_test()
39 static bool chi_square_test(int bins[256], int e) {  in chi_square_test()
44     // compute chi-square  in chi_square_test()
47         double delta = bins[j] - e;  in chi_square_test()
57     double t = ((-0.0004406*z*z* + 0.0418198)*z*z + 0.9)*z;  in normal_cdf()
58     t *= -1.77245385091;  // -sqrt(PI)  in normal_cdf()
65     int bins[256];  in test_random_byte()  local
66     memset(bins, 0, sizeof(int)*256);  in test_random_byte()
70         bins[(rand.nextU() >> shift) & 0xff]++;  in test_random_byte()
73     REPORTER_ASSERT(reporter, chi_square_test(bins, 10000));  in test_random_byte()
77     int bins[256];  in test_random_float()  local
78     memset(bins, 0, sizeof(int)*256);  in test_random_float()
84         bins[(int)(f*256.f)]++;  in test_random_float()
86     REPORTER_ASSERT(reporter, chi_square_test(bins, 10000));  in test_random_float()
102 // creating a z-score (# of deviations from the mean) for one iteration of this step
117     // pre-seed our string value  in test_single_gorilla()
119     for (int i = 0; i < kWordWidth-1; ++i) {  in test_single_gorilla()
131         int index = value & (kNumEntries-1);  in test_single_gorilla()
133         int entry_shift = (value >> (kWordWidth-5)) & 0x1f;  in test_single_gorilla()
147     // convert counts to normal distribution z-score  in test_single_gorilla()
148     double z = ((kN-total)-kMean)/kStandardDeviation;  in test_single_gorilla()
174     int bins[256];  in test_range()  local
175     memset(bins, 0, sizeof(int)*256);  in test_range()
179         bins[u - 17]++;  in test_range()
182     REPORTER_ASSERT(reporter, chi_square_test(bins, 10000));  in test_range()
186     // check uniform distributions of each byte in 32-bit word  in DEF_TEST()