xref: /aosp_15_r20/external/cronet/base/rand_util_unittest.cc (revision 6777b5387eb2ff775bb5750e3f5d96f37fb7352b)
1 // Copyright 2011 The Chromium Authors
2 // Use of this source code is governed by a BSD-style license that can be
3 // found in the LICENSE file.
4 
5 #include "base/rand_util.h"
6 
7 #include <stddef.h>
8 #include <stdint.h>
9 
10 #include <algorithm>
11 #include <cmath>
12 #include <limits>
13 #include <memory>
14 #include <vector>
15 
16 #include "base/containers/span.h"
17 #include "base/logging.h"
18 #include "base/time/time.h"
19 #include "testing/gtest/include/gtest/gtest.h"
20 
21 namespace base {
22 
23 namespace {
24 
25 const int kIntMin = std::numeric_limits<int>::min();
26 const int kIntMax = std::numeric_limits<int>::max();
27 
28 }  // namespace
29 
TEST(RandUtilTest,RandInt)30 TEST(RandUtilTest, RandInt) {
31   EXPECT_EQ(base::RandInt(0, 0), 0);
32   EXPECT_EQ(base::RandInt(kIntMin, kIntMin), kIntMin);
33   EXPECT_EQ(base::RandInt(kIntMax, kIntMax), kIntMax);
34 
35   // Check that the DCHECKS in RandInt() don't fire due to internal overflow.
36   // There was a 50% chance of that happening, so calling it 40 times means
37   // the chances of this passing by accident are tiny (9e-13).
38   for (int i = 0; i < 40; ++i)
39     base::RandInt(kIntMin, kIntMax);
40 }
41 
TEST(RandUtilTest,RandDouble)42 TEST(RandUtilTest, RandDouble) {
43   // Force 64-bit precision, making sure we're not in a 80-bit FPU register.
44   volatile double number = base::RandDouble();
45   EXPECT_GT(1.0, number);
46   EXPECT_LE(0.0, number);
47 }
48 
TEST(RandUtilTest,RandFloat)49 TEST(RandUtilTest, RandFloat) {
50   // Force 32-bit precision, making sure we're not in an 80-bit FPU register.
51   volatile float number = base::RandFloat();
52   EXPECT_GT(1.f, number);
53   EXPECT_LE(0.f, number);
54 }
55 
TEST(RandUtilTest,RandTimeDelta)56 TEST(RandUtilTest, RandTimeDelta) {
57   {
58     const auto delta =
59         base::RandTimeDelta(-base::Seconds(2), -base::Seconds(1));
60     EXPECT_GE(delta, -base::Seconds(2));
61     EXPECT_LT(delta, -base::Seconds(1));
62   }
63 
64   {
65     const auto delta = base::RandTimeDelta(-base::Seconds(2), base::Seconds(2));
66     EXPECT_GE(delta, -base::Seconds(2));
67     EXPECT_LT(delta, base::Seconds(2));
68   }
69 
70   {
71     const auto delta = base::RandTimeDelta(base::Seconds(1), base::Seconds(2));
72     EXPECT_GE(delta, base::Seconds(1));
73     EXPECT_LT(delta, base::Seconds(2));
74   }
75 }
76 
TEST(RandUtilTest,RandTimeDeltaUpTo)77 TEST(RandUtilTest, RandTimeDeltaUpTo) {
78   const auto delta = base::RandTimeDeltaUpTo(base::Seconds(2));
79   EXPECT_FALSE(delta.is_negative());
80   EXPECT_LT(delta, base::Seconds(2));
81 }
82 
TEST(RandUtilTest,BitsToOpenEndedUnitInterval)83 TEST(RandUtilTest, BitsToOpenEndedUnitInterval) {
84   // Force 64-bit precision, making sure we're not in an 80-bit FPU register.
85   volatile double all_zeros = BitsToOpenEndedUnitInterval(0x0);
86   EXPECT_EQ(0.0, all_zeros);
87 
88   // Force 64-bit precision, making sure we're not in an 80-bit FPU register.
89   volatile double smallest_nonzero = BitsToOpenEndedUnitInterval(0x1);
90   EXPECT_LT(0.0, smallest_nonzero);
91 
92   for (uint64_t i = 0x2; i < 0x10; ++i) {
93     // Force 64-bit precision, making sure we're not in an 80-bit FPU register.
94     volatile double number = BitsToOpenEndedUnitInterval(i);
95     EXPECT_EQ(i * smallest_nonzero, number);
96   }
97 
98   // Force 64-bit precision, making sure we're not in an 80-bit FPU register.
99   volatile double all_ones = BitsToOpenEndedUnitInterval(UINT64_MAX);
100   EXPECT_GT(1.0, all_ones);
101 }
102 
TEST(RandUtilTest,BitsToOpenEndedUnitIntervalF)103 TEST(RandUtilTest, BitsToOpenEndedUnitIntervalF) {
104   // Force 32-bit precision, making sure we're not in an 80-bit FPU register.
105   volatile float all_zeros = BitsToOpenEndedUnitIntervalF(0x0);
106   EXPECT_EQ(0.f, all_zeros);
107 
108   // Force 32-bit precision, making sure we're not in an 80-bit FPU register.
109   volatile float smallest_nonzero = BitsToOpenEndedUnitIntervalF(0x1);
110   EXPECT_LT(0.f, smallest_nonzero);
111 
112   for (uint64_t i = 0x2; i < 0x10; ++i) {
113     // Force 32-bit precision, making sure we're not in an 80-bit FPU register.
114     volatile float number = BitsToOpenEndedUnitIntervalF(i);
115     EXPECT_EQ(i * smallest_nonzero, number);
116   }
117 
118   // Force 32-bit precision, making sure we're not in an 80-bit FPU register.
119   volatile float all_ones = BitsToOpenEndedUnitIntervalF(UINT64_MAX);
120   EXPECT_GT(1.f, all_ones);
121 }
122 
TEST(RandUtilTest,RandBytes)123 TEST(RandUtilTest, RandBytes) {
124   const size_t buffer_size = 50;
125   uint8_t buffer[buffer_size];
126   memset(buffer, 0, buffer_size);
127   base::RandBytes(buffer);
128   std::sort(buffer, buffer + buffer_size);
129   // Probability of occurrence of less than 25 unique bytes in 50 random bytes
130   // is below 10^-25.
131   EXPECT_GT(std::unique(buffer, buffer + buffer_size) - buffer, 25);
132 }
133 
134 // Verify that calling base::RandBytes with an empty buffer doesn't fail.
TEST(RandUtilTest,RandBytes0)135 TEST(RandUtilTest, RandBytes0) {
136   base::RandBytes(span<uint8_t>());
137   base::RandBytes(nullptr, 0);
138 }
139 
TEST(RandUtilTest,RandBytesAsVector)140 TEST(RandUtilTest, RandBytesAsVector) {
141   std::vector<uint8_t> random_vec = base::RandBytesAsVector(0);
142   EXPECT_TRUE(random_vec.empty());
143   random_vec = base::RandBytesAsVector(1);
144   EXPECT_EQ(1U, random_vec.size());
145   random_vec = base::RandBytesAsVector(145);
146   EXPECT_EQ(145U, random_vec.size());
147   char accumulator = 0;
148   for (auto i : random_vec) {
149     accumulator |= i;
150   }
151   // In theory this test can fail, but it won't before the universe dies of
152   // heat death.
153   EXPECT_NE(0, accumulator);
154 }
155 
TEST(RandUtilTest,RandBytesAsString)156 TEST(RandUtilTest, RandBytesAsString) {
157   std::string random_string = base::RandBytesAsString(1);
158   EXPECT_EQ(1U, random_string.size());
159   random_string = base::RandBytesAsString(145);
160   EXPECT_EQ(145U, random_string.size());
161   char accumulator = 0;
162   for (auto i : random_string)
163     accumulator |= i;
164   // In theory this test can fail, but it won't before the universe dies of
165   // heat death.
166   EXPECT_NE(0, accumulator);
167 }
168 
169 // Make sure that it is still appropriate to use RandGenerator in conjunction
170 // with std::random_shuffle().
TEST(RandUtilTest,RandGeneratorForRandomShuffle)171 TEST(RandUtilTest, RandGeneratorForRandomShuffle) {
172   EXPECT_EQ(base::RandGenerator(1), 0U);
173   EXPECT_LE(std::numeric_limits<ptrdiff_t>::max(),
174             std::numeric_limits<int64_t>::max());
175 }
176 
TEST(RandUtilTest,RandGeneratorIsUniform)177 TEST(RandUtilTest, RandGeneratorIsUniform) {
178   // Verify that RandGenerator has a uniform distribution. This is a
179   // regression test that consistently failed when RandGenerator was
180   // implemented this way:
181   //
182   //   return base::RandUint64() % max;
183   //
184   // A degenerate case for such an implementation is e.g. a top of
185   // range that is 2/3rds of the way to MAX_UINT64, in which case the
186   // bottom half of the range would be twice as likely to occur as the
187   // top half. A bit of calculus care of jar@ shows that the largest
188   // measurable delta is when the top of the range is 3/4ths of the
189   // way, so that's what we use in the test.
190   constexpr uint64_t kTopOfRange =
191       (std::numeric_limits<uint64_t>::max() / 4ULL) * 3ULL;
192   constexpr double kExpectedAverage = static_cast<double>(kTopOfRange / 2);
193   constexpr double kAllowedVariance = kExpectedAverage / 50.0;  // +/- 2%
194   constexpr int kMinAttempts = 1000;
195   constexpr int kMaxAttempts = 1000000;
196 
197   double cumulative_average = 0.0;
198   int count = 0;
199   while (count < kMaxAttempts) {
200     uint64_t value = base::RandGenerator(kTopOfRange);
201     cumulative_average = (count * cumulative_average + value) / (count + 1);
202 
203     // Don't quit too quickly for things to start converging, or we may have
204     // a false positive.
205     if (count > kMinAttempts &&
206         kExpectedAverage - kAllowedVariance < cumulative_average &&
207         cumulative_average < kExpectedAverage + kAllowedVariance) {
208       break;
209     }
210 
211     ++count;
212   }
213 
214   ASSERT_LT(count, kMaxAttempts) << "Expected average was " << kExpectedAverage
215                                  << ", average ended at " << cumulative_average;
216 }
217 
TEST(RandUtilTest,RandUint64ProducesBothValuesOfAllBits)218 TEST(RandUtilTest, RandUint64ProducesBothValuesOfAllBits) {
219   // This tests to see that our underlying random generator is good
220   // enough, for some value of good enough.
221   uint64_t kAllZeros = 0ULL;
222   uint64_t kAllOnes = ~kAllZeros;
223   uint64_t found_ones = kAllZeros;
224   uint64_t found_zeros = kAllOnes;
225 
226   for (size_t i = 0; i < 1000; ++i) {
227     uint64_t value = base::RandUint64();
228     found_ones |= value;
229     found_zeros &= value;
230 
231     if (found_zeros == kAllZeros && found_ones == kAllOnes)
232       return;
233   }
234 
235   FAIL() << "Didn't achieve all bit values in maximum number of tries.";
236 }
237 
TEST(RandUtilTest,RandBytesLonger)238 TEST(RandUtilTest, RandBytesLonger) {
239   // Fuchsia can only retrieve 256 bytes of entropy at a time, so make sure we
240   // handle longer requests than that.
241   std::string random_string0 = base::RandBytesAsString(255);
242   EXPECT_EQ(255u, random_string0.size());
243   std::string random_string1 = base::RandBytesAsString(1023);
244   EXPECT_EQ(1023u, random_string1.size());
245   std::string random_string2 = base::RandBytesAsString(4097);
246   EXPECT_EQ(4097u, random_string2.size());
247 }
248 
249 // Benchmark test for RandBytes().  Disabled since it's intentionally slow and
250 // does not test anything that isn't already tested by the existing RandBytes()
251 // tests.
TEST(RandUtilTest,DISABLED_RandBytesPerf)252 TEST(RandUtilTest, DISABLED_RandBytesPerf) {
253   // Benchmark the performance of |kTestIterations| of RandBytes() using a
254   // buffer size of |kTestBufferSize|.
255   const int kTestIterations = 10;
256   const size_t kTestBufferSize = 1 * 1024 * 1024;
257 
258   std::unique_ptr<uint8_t[]> buffer(new uint8_t[kTestBufferSize]);
259   const base::TimeTicks now = base::TimeTicks::Now();
260   for (int i = 0; i < kTestIterations; ++i)
261     base::RandBytes(make_span(buffer.get(), kTestBufferSize));
262   const base::TimeTicks end = base::TimeTicks::Now();
263 
264   LOG(INFO) << "RandBytes(" << kTestBufferSize
265             << ") took: " << (end - now).InMicroseconds() << "µs";
266 }
267 
TEST(RandUtilTest,InsecureRandomGeneratorProducesBothValuesOfAllBits)268 TEST(RandUtilTest, InsecureRandomGeneratorProducesBothValuesOfAllBits) {
269   // This tests to see that our underlying random generator is good
270   // enough, for some value of good enough.
271   uint64_t kAllZeros = 0ULL;
272   uint64_t kAllOnes = ~kAllZeros;
273   uint64_t found_ones = kAllZeros;
274   uint64_t found_zeros = kAllOnes;
275 
276   InsecureRandomGenerator generator;
277 
278   for (size_t i = 0; i < 1000; ++i) {
279     uint64_t value = generator.RandUint64();
280     found_ones |= value;
281     found_zeros &= value;
282 
283     if (found_zeros == kAllZeros && found_ones == kAllOnes)
284       return;
285   }
286 
287   FAIL() << "Didn't achieve all bit values in maximum number of tries.";
288 }
289 
290 namespace {
291 
292 constexpr double kXp1Percent = -2.33;
293 constexpr double kXp99Percent = 2.33;
294 
ChiSquaredCriticalValue(double nu,double x_p)295 double ChiSquaredCriticalValue(double nu, double x_p) {
296   // From "The Art Of Computer Programming" (TAOCP), Volume 2, Section 3.3.1,
297   // Table 1. This is the asymptotic value for nu > 30, up to O(1 / sqrt(nu)).
298   return nu + sqrt(2. * nu) * x_p + 2. / 3. * (x_p * x_p) - 2. / 3.;
299 }
300 
ExtractBits(uint64_t value,int from_bit,int num_bits)301 int ExtractBits(uint64_t value, int from_bit, int num_bits) {
302   return (value >> from_bit) & ((1 << num_bits) - 1);
303 }
304 
305 // Performs a Chi-Squared test on a subset of |num_bits| extracted starting from
306 // |from_bit| in the generated value.
307 //
308 // See TAOCP, Volume 2, Section 3.3.1, and
309 // https://en.wikipedia.org/wiki/Pearson%27s_chi-squared_test for details.
310 //
311 // This is only one of the many, many random number generator test we could do,
312 // but they are cumbersome, as they are typically very slow, and expected to
313 // fail from time to time, due to their probabilistic nature.
314 //
315 // The generator we use has however been vetted with the BigCrush test suite
316 // from Marsaglia, so this should suffice as a smoke test that our
317 // implementation is wrong.
ChiSquaredTest(InsecureRandomGenerator & gen,size_t n,int from_bit,int num_bits)318 bool ChiSquaredTest(InsecureRandomGenerator& gen,
319                     size_t n,
320                     int from_bit,
321                     int num_bits) {
322   const int range = 1 << num_bits;
323   CHECK_EQ(static_cast<int>(n % range), 0) << "Makes computations simpler";
324   std::vector<size_t> samples(range, 0);
325 
326   // Count how many samples pf each value are found. All buckets should be
327   // almost equal if the generator is suitably uniformly random.
328   for (size_t i = 0; i < n; i++) {
329     int sample = ExtractBits(gen.RandUint64(), from_bit, num_bits);
330     samples[sample] += 1;
331   }
332 
333   // Compute the Chi-Squared statistic, which is:
334   // \Sum_{k=0}^{range-1} \frac{(count - expected)^2}{expected}
335   double chi_squared = 0.;
336   double expected_count = n / range;
337   for (size_t sample_count : samples) {
338     double deviation = sample_count - expected_count;
339     chi_squared += (deviation * deviation) / expected_count;
340   }
341 
342   // The generator should produce numbers that are not too far of (chi_squared
343   // lower than a given quantile), but not too close to the ideal distribution
344   // either (chi_squared is too low).
345   //
346   // See The Art Of Computer Programming, Volume 2, Section 3.3.1 for details.
347   return chi_squared > ChiSquaredCriticalValue(range - 1, kXp1Percent) &&
348          chi_squared < ChiSquaredCriticalValue(range - 1, kXp99Percent);
349 }
350 
351 }  // namespace
352 
TEST(RandUtilTest,InsecureRandomGeneratorChiSquared)353 TEST(RandUtilTest, InsecureRandomGeneratorChiSquared) {
354   constexpr int kIterations = 50;
355 
356   // Specifically test the low bits, which are usually weaker in random number
357   // generators. We don't use them for the 32 bit number generation, but let's
358   // make sure they are still suitable.
359   for (int start_bit : {1, 2, 3, 8, 12, 20, 32, 48, 54}) {
360     int pass_count = 0;
361     for (int i = 0; i < kIterations; i++) {
362       size_t samples = 1 << 16;
363       InsecureRandomGenerator gen;
364       // Fix the seed to make the test non-flaky.
365       gen.ReseedForTesting(kIterations + 1);
366       bool pass = ChiSquaredTest(gen, samples, start_bit, 8);
367       pass_count += pass;
368     }
369 
370     // We exclude 1% on each side, so we expect 98% of tests to pass, meaning 98
371     // * kIterations / 100. However this is asymptotic, so add a bit of leeway.
372     int expected_pass_count = (kIterations * 98) / 100;
373     EXPECT_GE(pass_count, expected_pass_count - ((kIterations * 2) / 100))
374         << "For start_bit = " << start_bit;
375   }
376 }
377 
TEST(RandUtilTest,InsecureRandomGeneratorRandDouble)378 TEST(RandUtilTest, InsecureRandomGeneratorRandDouble) {
379   InsecureRandomGenerator gen;
380 
381   for (int i = 0; i < 1000; i++) {
382     volatile double x = gen.RandDouble();
383     EXPECT_GE(x, 0.);
384     EXPECT_LT(x, 1.);
385   }
386 }
387 
TEST(RandUtilTest,MetricsSubSampler)388 TEST(RandUtilTest, MetricsSubSampler) {
389   MetricsSubSampler sub_sampler;
390   int true_count = 0;
391   int false_count = 0;
392   for (int i = 0; i < 1000; ++i) {
393     if (sub_sampler.ShouldSample(0.5)) {
394       ++true_count;
395     } else {
396       ++false_count;
397     }
398   }
399 
400   // Validate that during normal operation MetricsSubSampler::ShouldSample()
401   // does not always give the same result. It's technically possible to fail
402   // this test during normal operation but if the sampling is realistic it
403   // should happen about once every 2^999 times (the likelihood of the [1,999]
404   // results being the same as [0], which can be either). This should not make
405   // this test flaky in the eyes of automated testing.
406   EXPECT_GT(true_count, 0);
407   EXPECT_GT(false_count, 0);
408 }
409 
TEST(RandUtilTest,MetricsSubSamplerTestingSupport)410 TEST(RandUtilTest, MetricsSubSamplerTestingSupport) {
411   MetricsSubSampler sub_sampler;
412 
413   // ScopedAlwaysSampleForTesting makes ShouldSample() return true with
414   // any probability.
415   {
416     MetricsSubSampler::ScopedAlwaysSampleForTesting always_sample;
417     for (int i = 0; i < 100; ++i) {
418       EXPECT_TRUE(sub_sampler.ShouldSample(0));
419       EXPECT_TRUE(sub_sampler.ShouldSample(0.5));
420       EXPECT_TRUE(sub_sampler.ShouldSample(1));
421     }
422   }
423 
424   // ScopedNeverSampleForTesting makes ShouldSample() return true with
425   // any probability.
426   {
427     MetricsSubSampler::ScopedNeverSampleForTesting always_sample;
428     for (int i = 0; i < 100; ++i) {
429       EXPECT_FALSE(sub_sampler.ShouldSample(0));
430       EXPECT_FALSE(sub_sampler.ShouldSample(0.5));
431       EXPECT_FALSE(sub_sampler.ShouldSample(1));
432     }
433   }
434 }
435 
436 }  // namespace base
437