1 // Copyright 2017 The Abseil Authors.
2 //
3 // Licensed under the Apache License, Version 2.0 (the "License");
4 // you may not use this file except in compliance with the License.
5 // You may obtain a copy of the License at
6 //
7 //      https://www.apache.org/licenses/LICENSE-2.0
8 //
9 // Unless required by applicable law or agreed to in writing, software
10 // distributed under the License is distributed on an "AS IS" BASIS,
11 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 // See the License for the specific language governing permissions and
13 // limitations under the License.
14 
15 #include "absl/random/uniform_int_distribution.h"
16 
17 #include <cmath>
18 #include <cstdint>
19 #include <iterator>
20 #include <random>
21 #include <sstream>
22 #include <string>
23 #include <vector>
24 
25 #include "gmock/gmock.h"
26 #include "gtest/gtest.h"
27 #include "absl/base/internal/raw_logging.h"
28 #include "absl/random/internal/chi_square.h"
29 #include "absl/random/internal/distribution_test_util.h"
30 #include "absl/random/internal/pcg_engine.h"
31 #include "absl/random/internal/sequence_urbg.h"
32 #include "absl/random/random.h"
33 #include "absl/strings/str_cat.h"
34 
35 namespace {
36 
37 template <typename IntType>
38 class UniformIntDistributionTest : public ::testing::Test {};
39 
40 using IntTypes = ::testing::Types<int8_t, uint8_t, int16_t, uint16_t, int32_t,
41                                   uint32_t, int64_t, uint64_t>;
42 TYPED_TEST_SUITE(UniformIntDistributionTest, IntTypes);
43 
TYPED_TEST(UniformIntDistributionTest,ParamSerializeTest)44 TYPED_TEST(UniformIntDistributionTest, ParamSerializeTest) {
45   // This test essentially ensures that the parameters serialize,
46   // not that the values generated cover the full range.
47   using Limits = std::numeric_limits<TypeParam>;
48   using param_type =
49       typename absl::uniform_int_distribution<TypeParam>::param_type;
50   const TypeParam kMin = std::is_unsigned<TypeParam>::value ? 37 : -105;
51   const TypeParam kNegOneOrZero = std::is_unsigned<TypeParam>::value ? 0 : -1;
52 
53   constexpr int kCount = 1000;
54   absl::InsecureBitGen gen;
55   for (const auto& param : {
56            param_type(),
57            param_type(2, 2),  // Same
58            param_type(9, 32),
59            param_type(kMin, 115),
60            param_type(kNegOneOrZero, Limits::max()),
61            param_type(Limits::min(), Limits::max()),
62            param_type(Limits::lowest(), Limits::max()),
63            param_type(Limits::min() + 1, Limits::max() - 1),
64        }) {
65     const auto a = param.a();
66     const auto b = param.b();
67     absl::uniform_int_distribution<TypeParam> before(a, b);
68     EXPECT_EQ(before.a(), param.a());
69     EXPECT_EQ(before.b(), param.b());
70 
71     {
72       // Initialize via param_type
73       absl::uniform_int_distribution<TypeParam> via_param(param);
74       EXPECT_EQ(via_param, before);
75     }
76 
77     // Initialize via iostreams
78     std::stringstream ss;
79     ss << before;
80 
81     absl::uniform_int_distribution<TypeParam> after(Limits::min() + 3,
82                                                     Limits::max() - 5);
83 
84     EXPECT_NE(before.a(), after.a());
85     EXPECT_NE(before.b(), after.b());
86     EXPECT_NE(before.param(), after.param());
87     EXPECT_NE(before, after);
88 
89     ss >> after;
90 
91     EXPECT_EQ(before.a(), after.a());
92     EXPECT_EQ(before.b(), after.b());
93     EXPECT_EQ(before.param(), after.param());
94     EXPECT_EQ(before, after);
95 
96     // Smoke test.
97     auto sample_min = after.max();
98     auto sample_max = after.min();
99     for (int i = 0; i < kCount; i++) {
100       auto sample = after(gen);
101       EXPECT_GE(sample, after.min());
102       EXPECT_LE(sample, after.max());
103       if (sample > sample_max) {
104         sample_max = sample;
105       }
106       if (sample < sample_min) {
107         sample_min = sample;
108       }
109     }
110     std::string msg = absl::StrCat("Range: ", +sample_min, ", ", +sample_max);
111     ABSL_RAW_LOG(INFO, "%s", msg.c_str());
112   }
113 }
114 
TYPED_TEST(UniformIntDistributionTest,ViolatesPreconditionsDeathTest)115 TYPED_TEST(UniformIntDistributionTest, ViolatesPreconditionsDeathTest) {
116 #if GTEST_HAS_DEATH_TEST
117   // Hi < Lo
118   EXPECT_DEBUG_DEATH({ absl::uniform_int_distribution<TypeParam> dist(10, 1); },
119                      "");
120 #endif  // GTEST_HAS_DEATH_TEST
121 #if defined(NDEBUG)
122   // opt-mode, for invalid parameters, will generate a garbage value,
123   // but should not enter an infinite loop.
124   absl::InsecureBitGen gen;
125   absl::uniform_int_distribution<TypeParam> dist(10, 1);
126   auto x = dist(gen);
127 
128   // Any value will generate a non-empty string.
129   EXPECT_FALSE(absl::StrCat(+x).empty()) << x;
130 #endif  // NDEBUG
131 }
132 
TYPED_TEST(UniformIntDistributionTest,TestMoments)133 TYPED_TEST(UniformIntDistributionTest, TestMoments) {
134   constexpr int kSize = 100000;
135   using Limits = std::numeric_limits<TypeParam>;
136   using param_type =
137       typename absl::uniform_int_distribution<TypeParam>::param_type;
138 
139   // We use a fixed bit generator for distribution accuracy tests.  This allows
140   // these tests to be deterministic, while still testing the quality of the
141   // implementation.
142   absl::random_internal::pcg64_2018_engine rng{0x2B7E151628AED2A6};
143 
144   std::vector<double> values(kSize);
145   for (const auto& param :
146        {param_type(0, Limits::max()), param_type(13, 127)}) {
147     absl::uniform_int_distribution<TypeParam> dist(param);
148     for (int i = 0; i < kSize; i++) {
149       const auto sample = dist(rng);
150       ASSERT_LE(dist.param().a(), sample);
151       ASSERT_GE(dist.param().b(), sample);
152       values[i] = sample;
153     }
154 
155     auto moments = absl::random_internal::ComputeDistributionMoments(values);
156     const double a = dist.param().a();
157     const double b = dist.param().b();
158     const double n = (b - a + 1);
159     const double mean = (a + b) / 2;
160     const double var = ((b - a + 1) * (b - a + 1) - 1) / 12;
161     const double kurtosis = 3 - 6 * (n * n + 1) / (5 * (n * n - 1));
162 
163     // TODO(ahh): this is not the right bound
164     // empirically validated with --runs_per_test=10000.
165     EXPECT_NEAR(mean, moments.mean, 0.01 * var);
166     EXPECT_NEAR(var, moments.variance, 0.015 * var);
167     EXPECT_NEAR(0.0, moments.skewness, 0.025);
168     EXPECT_NEAR(kurtosis, moments.kurtosis, 0.02 * kurtosis);
169   }
170 }
171 
TYPED_TEST(UniformIntDistributionTest,ChiSquaredTest50)172 TYPED_TEST(UniformIntDistributionTest, ChiSquaredTest50) {
173   using absl::random_internal::kChiSquared;
174 
175   constexpr size_t kTrials = 1000;
176   constexpr int kBuckets = 50;  // inclusive, so actually +1
177   constexpr double kExpected =
178       static_cast<double>(kTrials) / static_cast<double>(kBuckets);
179 
180   // Empirically validated with --runs_per_test=10000.
181   const int kThreshold =
182       absl::random_internal::ChiSquareValue(kBuckets, 0.999999);
183 
184   const TypeParam min = std::is_unsigned<TypeParam>::value ? 37 : -37;
185   const TypeParam max = min + kBuckets;
186 
187   // We use a fixed bit generator for distribution accuracy tests.  This allows
188   // these tests to be deterministic, while still testing the quality of the
189   // implementation.
190   absl::random_internal::pcg64_2018_engine rng{0x2B7E151628AED2A6};
191 
192   absl::uniform_int_distribution<TypeParam> dist(min, max);
193 
194   std::vector<int32_t> counts(kBuckets + 1, 0);
195   for (size_t i = 0; i < kTrials; i++) {
196     auto x = dist(rng);
197     counts[x - min]++;
198   }
199   double chi_square = absl::random_internal::ChiSquareWithExpected(
200       std::begin(counts), std::end(counts), kExpected);
201   if (chi_square > kThreshold) {
202     double p_value =
203         absl::random_internal::ChiSquarePValue(chi_square, kBuckets);
204 
205     // Chi-squared test failed. Output does not appear to be uniform.
206     std::string msg;
207     for (const auto& a : counts) {
208       absl::StrAppend(&msg, a, "\n");
209     }
210     absl::StrAppend(&msg, kChiSquared, " p-value ", p_value, "\n");
211     absl::StrAppend(&msg, "High ", kChiSquared, " value: ", chi_square, " > ",
212                     kThreshold);
213     ABSL_RAW_LOG(INFO, "%s", msg.c_str());
214     FAIL() << msg;
215   }
216 }
217 
TEST(UniformIntDistributionTest,StabilityTest)218 TEST(UniformIntDistributionTest, StabilityTest) {
219   // absl::uniform_int_distribution stability relies only on integer operations.
220   absl::random_internal::sequence_urbg urbg(
221       {0x0003eb76f6f7f755ull, 0xFFCEA50FDB2F953Bull, 0xC332DDEFBE6C5AA5ull,
222        0x6558218568AB9702ull, 0x2AEF7DAD5B6E2F84ull, 0x1521B62829076170ull,
223        0xECDD4775619F1510ull, 0x13CCA830EB61BD96ull, 0x0334FE1EAA0363CFull,
224        0xB5735C904C70A239ull, 0xD59E9E0BCBAADE14ull, 0xEECC86BC60622CA7ull});
225 
226   std::vector<int> output(12);
227 
228   {
229     absl::uniform_int_distribution<int32_t> dist(0, 4);
230     for (auto& v : output) {
231       v = dist(urbg);
232     }
233   }
234   EXPECT_EQ(12, urbg.invocations());
235   EXPECT_THAT(output, testing::ElementsAre(4, 4, 3, 2, 1, 0, 1, 4, 3, 1, 3, 1));
236 
237   {
238     urbg.reset();
239     absl::uniform_int_distribution<int32_t> dist(0, 100);
240     for (auto& v : output) {
241       v = dist(urbg);
242     }
243   }
244   EXPECT_EQ(12, urbg.invocations());
245   EXPECT_THAT(output, testing::ElementsAre(97, 86, 75, 41, 36, 16, 38, 92, 67,
246                                            30, 80, 38));
247 
248   {
249     urbg.reset();
250     absl::uniform_int_distribution<int32_t> dist(0, 10000);
251     for (auto& v : output) {
252       v = dist(urbg);
253     }
254   }
255   EXPECT_EQ(12, urbg.invocations());
256   EXPECT_THAT(output, testing::ElementsAre(9648, 8562, 7439, 4089, 3571, 1602,
257                                            3813, 9195, 6641, 2986, 7956, 3765));
258 }
259 
260 }  // namespace
261