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1 // Copyright (c) 2012 The Chromium Authors. All rights reserved. | |
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 <limits> | |
6 | |
7 #include "base/basictypes.h" | |
8 #include "base/memory/scoped_ptr.h" | |
9 #include "base/rand_util.h" | |
10 #include "base/string_number_conversions.h" | |
11 #include "chrome/common/metrics/entropy_provider.h" | |
12 #include "testing/gtest/include/gtest/gtest.h" | |
13 | |
14 class EntropyProviderTest : public testing::Test { | |
15 public: | |
16 // Computes SHA1-based entropy for the given |trial_name| based on | |
17 // |entropy_source| | |
18 double GenerateSHA1Entropy(const std::string& entropy_source, | |
19 const std::string& trial_name) { | |
20 SHA1EntropyProvider sha1_provider(entropy_source); | |
21 return sha1_provider.GetEntropyForTrial(trial_name); | |
22 } | |
23 | |
24 // Generates permutation-based entropy for the given |trial_name| based on | |
25 // |entropy_source| which must be in the range [0, entropy_max). | |
26 double GeneratePermutedEntropy(uint16 entropy_source, | |
27 size_t entropy_max, | |
28 const std::string& trial_name) { | |
29 PermutedEntropyProvider permuted_provider(entropy_source, entropy_max); | |
30 return permuted_provider.GetEntropyForTrial(trial_name); | |
31 } | |
32 }; | |
33 | |
34 | |
35 TEST_F(EntropyProviderTest, UseOneTimeRandomizationSHA1) { | |
36 // Simply asserts that two trials using one-time randomization | |
37 // that have different names, normally generate different results. | |
38 // | |
39 // Note that depending on the one-time random initialization, they | |
40 // _might_ actually give the same result, but we know that given | |
41 // the particular client_id we use for unit tests they won't. | |
42 base::FieldTrialList field_trial_list(new SHA1EntropyProvider("client_id")); | |
43 scoped_refptr<base::FieldTrial> trials[] = { | |
44 base::FieldTrialList::FactoryGetFieldTrial("one", 100, "default", | |
jar (doing other things)
2012/08/17 19:06:19
nit: 4 character indent (I think) for this line ov
Alexei Svitkine (slow)
2012/08/20 15:57:40
Done.
| |
45 base::FieldTrialList::kExpirationYearInFuture, 1, 1, NULL), | |
46 base::FieldTrialList::FactoryGetFieldTrial("two", 100, "default", | |
47 base::FieldTrialList::kExpirationYearInFuture, 1, 1, NULL), | |
48 }; | |
jar (doing other things)
2012/08/17 19:06:19
nit: This curly is not a block closure, and is mor
Alexei Svitkine (slow)
2012/08/20 15:57:40
That suggestion doesn't seem consistent with the s
jar (doing other things)
2012/08/23 01:38:30
I checked with BrettW, and WillChan (Google readab
Alexei Svitkine (slow)
2012/08/23 15:10:43
Done.
| |
49 | |
50 for (size_t i = 0; i < arraysize(trials); ++i) { | |
51 trials[i]->UseOneTimeRandomization(); | |
52 | |
53 for (int j = 0; j < 100; ++j) | |
54 trials[i]->AppendGroup("", 1); | |
55 } | |
56 | |
57 // The trials are most likely to give different results since they have | |
58 // different names. | |
59 ASSERT_NE(trials[0]->group(), trials[1]->group()); | |
60 ASSERT_NE(trials[0]->group_name(), trials[1]->group_name()); | |
61 } | |
62 | |
63 TEST_F(EntropyProviderTest, UseOneTimeRandomizationPermuted) { | |
64 // Simply asserts that two trials using one-time randomization | |
65 // that have different names, normally generate different results. | |
66 // | |
67 // Note that depending on the one-time random initialization, they | |
68 // _might_ actually give the same result, but we know that given | |
69 // the particular client_id we use for unit tests they won't. | |
70 const size_t kMaxEntropySize = (1 << 13); | |
71 base::FieldTrialList field_trial_list( | |
72 new PermutedEntropyProvider(1234, kMaxEntropySize)); | |
73 scoped_refptr<base::FieldTrial> trials[] = { | |
74 base::FieldTrialList::FactoryGetFieldTrial("one", 100, "default", | |
jar (doing other things)
2012/08/17 19:06:19
nit: 4 character indent
Alexei Svitkine (slow)
2012/08/20 15:57:40
Done.
| |
75 base::FieldTrialList::kExpirationYearInFuture, 1, 1, NULL), | |
76 base::FieldTrialList::FactoryGetFieldTrial("two", 100, "default", | |
77 base::FieldTrialList::kExpirationYearInFuture, 1, 1, NULL), | |
78 }; | |
jar (doing other things)
2012/08/17 19:06:19
nit: This curly is not a block closure, and is mor
Alexei Svitkine (slow)
2012/08/20 15:57:40
That suggestion doesn't seem consistent with the s
| |
79 | |
80 for (size_t i = 0; i < arraysize(trials); ++i) { | |
81 trials[i]->UseOneTimeRandomization(); | |
82 | |
83 for (int j = 0; j < 100; ++j) | |
84 trials[i]->AppendGroup("", 1); | |
85 } | |
86 | |
87 // The trials are most likely to give different results since they have | |
88 // different names. | |
89 ASSERT_NE(trials[0]->group(), trials[1]->group()); | |
90 ASSERT_NE(trials[0]->group_name(), trials[1]->group_name()); | |
91 } | |
92 | |
93 TEST_F(EntropyProviderTest, SHA1Entropy) { | |
94 double results[] = { | |
95 GenerateSHA1Entropy("hi", "1"), | |
jar (doing other things)
2012/08/17 19:06:19
nit: indent 4.
Alexei Svitkine (slow)
2012/08/20 15:57:40
Done.
| |
96 GenerateSHA1Entropy("there", "1"), | |
97 }; | |
98 ASSERT_NE(results[0], results[1]); | |
99 for (size_t i = 0; i < arraysize(results); ++i) { | |
100 ASSERT_LE(0.0, results[i]); | |
101 ASSERT_GT(1.0, results[i]); | |
102 } | |
103 | |
104 ASSERT_EQ(GenerateSHA1Entropy("yo", "1"), | |
105 GenerateSHA1Entropy("yo", "1")); | |
106 ASSERT_NE(GenerateSHA1Entropy("yo", "something"), | |
107 GenerateSHA1Entropy("yo", "else")); | |
108 } | |
109 | |
110 TEST_F(EntropyProviderTest, PermutedEntropy) { | |
111 const size_t kMaxEntropySize = (1 << 13); | |
112 double results[] = { | |
113 GeneratePermutedEntropy(1234, kMaxEntropySize, "1"), | |
114 GeneratePermutedEntropy(4321, kMaxEntropySize, "1"), | |
115 }; | |
116 ASSERT_NE(results[0], results[1]); | |
117 for (size_t i = 0; i < arraysize(results); ++i) { | |
118 ASSERT_LE(0.0, results[i]); | |
119 ASSERT_GT(1.0, results[i]); | |
120 } | |
121 | |
122 ASSERT_EQ(GeneratePermutedEntropy(1234, kMaxEntropySize, "1"), | |
123 GeneratePermutedEntropy(1234, kMaxEntropySize, "1")); | |
124 ASSERT_NE(GeneratePermutedEntropy(1234, kMaxEntropySize, "something"), | |
125 GeneratePermutedEntropy(1234, kMaxEntropySize, "else")); | |
126 } | |
127 | |
128 TEST_F(EntropyProviderTest, SHA1EntropyIsUniform) { | |
129 // Choose a random start number but go sequentially from there, so | |
130 // that each test tries a different range but we never provide uniformly | |
131 // distributed input data. | |
132 int current_number = base::RandInt(0, std::numeric_limits<int>::max()); | |
133 | |
134 // The expected value of a random distribution is the average over all | |
135 // samples as the number of samples approaches infinity. For a uniform | |
136 // distribution from [0.0, 1.0) this would be 0.5. | |
137 // | |
138 // We do kSamplesBetweenChecks at a time and check if the value has converged | |
139 // to a narrow interval around 0.5. A non-uniform distribution would likely | |
140 // converge at something different, or not converge consistently within this | |
141 // range (i.e. the test would start timing out occasionally). | |
142 int kSamplesBetweenChecks = 300; | |
143 int num_samples = 0; | |
144 double total_value = 0.0; | |
145 while (true) { | |
146 for (int i = 0; i < kSamplesBetweenChecks; ++i) { | |
147 total_value += GenerateSHA1Entropy( | |
148 base::IntToString(current_number++), "salt"); | |
149 num_samples++; | |
150 } | |
151 | |
152 double average = total_value / num_samples; | |
153 double kExpectedMin = 0.48; | |
154 double kExpectedMax = 0.52; | |
155 | |
156 if (num_samples > 1000 && | |
157 (average < kExpectedMin || average > kExpectedMax)) { | |
158 // Only printed once we have enough samples that it's very unlikely | |
159 // things haven't converged. | |
160 printf("After %d samples, the average was %f, outside the expected\n" | |
161 "range (%f, %f). We will add more samples and check after every\n" | |
162 "%d samples. If the average does not converge, something\n" | |
163 "is broken. If it does converge, the test will pass.\n", | |
164 num_samples, average, | |
165 kExpectedMin, kExpectedMax, kSamplesBetweenChecks); | |
166 } else { | |
167 // Success. | |
168 break; | |
169 } | |
170 } | |
171 } | |
172 | |
173 TEST_F(EntropyProviderTest, PermutedEntropyIsUniform) { | |
174 // Choose a random start number but go sequentially from there, so | |
175 // that each test tries a different range but we never provide uniformly | |
176 // distributed input data. | |
177 const size_t kMaxEntropySize = (1 << 13); | |
178 int current_number = base::RandInt(0, kMaxEntropySize - 1); | |
179 | |
180 // The expected value of a random distribution is the average over all | |
181 // samples as the number of samples approaches infinity. For a uniform | |
182 // distribution from [0.0, 1.0) this would be 0.5. | |
hfung
2012/08/17 17:35:40
So you aren't testing the distribution among diffe
Alexei Svitkine (slow)
2012/08/17 17:57:40
Ilya had the same concern / suggestion. (Note: Thi
| |
183 // | |
184 // We do kSamplesBetweenChecks at a time and check if the value has converged | |
185 // to a narrow interval around 0.5. A non-uniform distribution would likely | |
186 // converge at something different, or not converge consistently within this | |
187 // range (i.e. the test would start timing out occasionally). | |
188 int kSamplesBetweenChecks = 300; | |
189 int num_samples = 0; | |
190 double total_value = 0.0; | |
191 while (true) { | |
192 for (int i = 0; i < kSamplesBetweenChecks; ++i) { | |
193 total_value += GeneratePermutedEntropy(current_number++ % kMaxEntropySize, | |
194 kMaxEntropySize, "salt"); | |
195 num_samples++; | |
196 } | |
197 | |
198 double average = total_value / num_samples; | |
199 double kExpectedMin = 0.48; | |
200 double kExpectedMax = 0.52; | |
201 | |
202 if (num_samples > 1000 && | |
203 (average < kExpectedMin || average > kExpectedMax)) { | |
204 // Only printed once we have enough samples that it's very unlikely | |
205 // things haven't converged. | |
206 printf("After %d samples, the average was %f, outside the expected\n" | |
207 "range (%f, %f). We will add more samples and check after every\n" | |
208 "%d samples. If the average does not converge, something\n" | |
209 "is broken. If it does converge, the test will pass.\n", | |
210 num_samples, average, | |
211 kExpectedMin, kExpectedMax, kSamplesBetweenChecks); | |
212 } else { | |
213 // Success. | |
214 break; | |
215 } | |
216 } | |
217 } | |
218 | |
219 TEST_F(EntropyProviderTest, SeededRandGeneratorIsUniform) { | |
220 // Verifies. that SeededRandGenerator has a uniform distribution. | |
hfung
2012/08/17 17:35:40
extra period?
Alexei Svitkine (slow)
2012/08/17 17:57:40
Done.
| |
221 // | |
222 // Mirrors RandUtilTest.RandGeneratorIsUniform in base/rand_util_unittest.cc. | |
223 | |
224 const uint32 kTopOfRange = (std::numeric_limits<uint32>::max() / 4ULL) * 3ULL; | |
225 const uint32 kExpectedAverage = kTopOfRange / 2ULL; | |
226 const uint32 kAllowedVariance = kExpectedAverage / 50ULL; // +/- 2% | |
227 const int kMinAttempts = 1000; | |
228 const int kMaxAttempts = 1000000; | |
229 | |
230 const std::string trial_names[] = { | |
231 "TestTrial", | |
232 "AnotherTestTrial", | |
233 "NewTabButton", | |
234 }; | |
235 | |
236 for (size_t i = 0; i < arraysize(trial_names); ++i) { | |
237 const uint32 seed = internal::HashName(trial_names[i]); | |
238 internal::SeededRandGenerator rand_generator(seed); | |
239 | |
240 double cumulative_average = 0.0; | |
241 int count = 0; | |
242 while (count < kMaxAttempts) { | |
243 uint32 value = rand_generator(kTopOfRange); | |
244 cumulative_average = (count * cumulative_average + value) / (count + 1); | |
245 | |
246 // Don't quit too quickly for things to start converging, or we may have | |
247 // a false positive. | |
248 if (count > kMinAttempts && | |
249 kExpectedAverage - kAllowedVariance < cumulative_average && | |
250 cumulative_average < kExpectedAverage + kAllowedVariance) { | |
251 break; | |
252 } | |
253 | |
254 ++count; | |
255 } | |
256 | |
257 ASSERT_LT(count, kMaxAttempts) << "Expected average was " << | |
258 kExpectedAverage << ", average ended at " << cumulative_average; | |
259 } | |
260 } | |
261 | |
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