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// Copyright 2012 The Chromium Authors
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.
#include "components/variations/entropy_provider.h"
#include <stddef.h>
#include <stdint.h>
#include <array>
#include <cmath>
#include <limits>
#include <memory>
#include <numeric>
#include "base/rand_util.h"
#include "base/strings/string_number_conversions.h"
#include "base/test/scoped_feature_list.h"
#include "base/uuid.h"
#include "components/variations/hashing.h"
#include "testing/gtest/include/gtest/gtest.h"
namespace variations {
namespace {
// Size of the low entropy source for testing.
const uint32_t kMaxLowEntropySize = 8000;
// Field trial names used in unit tests.
const char* const kTestTrialNames[] = { "TestTrial", "AnotherTestTrial",
"NewTabButton" };
// Computes the Chi-Square statistic for |values| assuming they follow a uniform
// distribution, where each entry has expected value |expected_value|.
//
// The Chi-Square statistic is defined as Sum((O-E)^2/E) where O is the observed
// value and E is the expected value.
double ComputeChiSquare(const std::vector<int>& values,
double expected_value) {
double sum = 0;
for (size_t i = 0; i < values.size(); ++i) {
const double delta = values[i] - expected_value;
sum += (delta * delta) / expected_value;
}
return sum;
}
// Computes SHA1-based entropy for the given |trial_name| based on
// |entropy_source|
double GenerateSHA1Entropy(const std::string& entropy_source,
const std::string& trial_name) {
SHA1EntropyProvider sha1_provider(entropy_source);
return sha1_provider.GetEntropyForTrial(trial_name, 0);
}
// Generates normalized MurmurHash-based entropy for the given |trial_name|
// based on |entropy_source| which must be in the range [0, entropy_max).
double GenerateNormalizedMurmurHashEntropy(ValueInRange entropy_source,
const std::string& trial_name) {
NormalizedMurmurHashEntropyProvider provider(entropy_source);
return provider.GetEntropyForTrial(trial_name, 0);
}
// Helper interface for testing used to generate entropy values for a given
// field trial. Unlike EntropyProvider, which keeps the low/high entropy source
// value constant and generates entropy for different trial names, instances
// of TrialEntropyGenerator keep the trial name constant and generate low/high
// entropy source values internally to produce each output entropy value.
class TrialEntropyGenerator {
public:
virtual ~TrialEntropyGenerator() = default;
virtual double GenerateEntropyValue() const = 0;
};
// An TrialEntropyGenerator that uses the SHA1EntropyProvider with the high
// entropy source (random UUID with 128 bits of entropy + 13 additional bits of
// entropy corresponding to a low entropy source).
class SHA1EntropyGenerator : public TrialEntropyGenerator {
public:
explicit SHA1EntropyGenerator(const std::string& trial_name)
: trial_name_(trial_name) {
}
SHA1EntropyGenerator(const SHA1EntropyGenerator&) = delete;
SHA1EntropyGenerator& operator=(const SHA1EntropyGenerator&) = delete;
~SHA1EntropyGenerator() override = default;
double GenerateEntropyValue() const override {
// Use a random UUID + 13 additional bits of entropy to match how the
// SHA1EntropyProvider is used in metrics_service.cc.
const int low_entropy_source =
static_cast<uint16_t>(base::RandInt(0, kMaxLowEntropySize - 1));
const std::string high_entropy_source =
base::Uuid::GenerateRandomV4().AsLowercaseString() +
base::NumberToString(low_entropy_source);
return GenerateSHA1Entropy(high_entropy_source, trial_name_);
}
private:
const std::string trial_name_;
};
// An TrialEntropyGenerator that uses the normalized MurmurHash entropy provider
// algorithm, using 13-bit low entropy source values.
class NormalizedMurmurHashEntropyGenerator : public TrialEntropyGenerator {
public:
explicit NormalizedMurmurHashEntropyGenerator(const std::string& trial_name)
: trial_name_(trial_name) {}
NormalizedMurmurHashEntropyGenerator(
const NormalizedMurmurHashEntropyGenerator&) = delete;
NormalizedMurmurHashEntropyGenerator& operator=(
const NormalizedMurmurHashEntropyGenerator&) = delete;
~NormalizedMurmurHashEntropyGenerator() override = default;
double GenerateEntropyValue() const override {
return GenerateNormalizedMurmurHashEntropy(
{
.value =
static_cast<uint32_t>(base::RandInt(0, kMaxLowEntropySize - 1)),
.range = kMaxLowEntropySize,
},
trial_name_);
}
private:
const std::string trial_name_;
};
// Tests uniformity of a given |entropy_generator| using the Chi-Square Goodness
// of Fit Test.
void PerformEntropyUniformityTest(
const std::string& trial_name,
const TrialEntropyGenerator& entropy_generator) {
// Number of buckets in the simulated field trials.
const size_t kBucketCount = 20;
// Max number of iterations to perform before giving up and failing.
const size_t kMaxIterationCount = 100000;
// The number of iterations to perform before each time the statistical
// significance of the results is checked.
const size_t kCheckIterationCount = 10000;
// This is the Chi-Square threshold from the Chi-Square statistic table for
// 19 degrees of freedom (based on |kBucketCount|) with a 99.9% confidence
// level. See: http://www.medcalc.org/manual/chi-square-table.php
const double kChiSquareThreshold = 43.82;
std::vector<int> distribution(kBucketCount);
for (size_t i = 1; i <= kMaxIterationCount; ++i) {
const double entropy_value = entropy_generator.GenerateEntropyValue();
const size_t bucket = static_cast<size_t>(kBucketCount * entropy_value);
ASSERT_LT(bucket, kBucketCount);
distribution[bucket] += 1;
// After |kCheckIterationCount| iterations, compute the Chi-Square
// statistic of the distribution. If the resulting statistic is greater
// than |kChiSquareThreshold|, we can conclude with 99.9% confidence
// that the observed samples do not follow a uniform distribution.
//
// However, since 99.9% would still result in a false negative every
// 1000 runs of the test, do not treat it as a failure (else the test
// will be flaky). Instead, perform additional iterations to determine
// if the distribution will converge, up to |kMaxIterationCount|.
if ((i % kCheckIterationCount) == 0) {
const double expected_value_per_bucket =
static_cast<double>(i) / kBucketCount;
const double chi_square =
ComputeChiSquare(distribution, expected_value_per_bucket);
if (chi_square < kChiSquareThreshold)
break;
// If |i == kMaxIterationCount|, the Chi-Square statistic did not
// converge after |kMaxIterationCount|.
EXPECT_NE(i, kMaxIterationCount) << "Failed for trial " <<
trial_name << " with chi_square = " << chi_square <<
" after " << kMaxIterationCount << " iterations.";
}
}
}
} // namespace
TEST(EntropyProviderTest, UseOneTimeRandomizationSHA1) {
// Simply asserts that two trials using one-time randomization
// that have different names, normally generate different results.
//
// Note that depending on the one-time random initialization, they
// _might_ actually give the same result, but we know that given the
// particular client_id we use for unit tests they won't.
SHA1EntropyProvider entropy_provider("client_id");
auto trials = std::to_array<scoped_refptr<base::FieldTrial>>({
base::FieldTrialList::FactoryGetFieldTrial("one", 100, "default",
entropy_provider),
base::FieldTrialList::FactoryGetFieldTrial("two", 100, "default",
entropy_provider),
});
for (const scoped_refptr<base::FieldTrial>& trial : trials) {
for (int j = 0; j < 100; ++j)
trial->AppendGroup(std::string(), 1);
}
// The trials are most likely to give different results since they have
// different names.
EXPECT_NE(trials[0]->group_name(), trials[1]->group_name());
}
TEST(EntropyProviderTest, UseOneTimeRandomizationNormalizedMurmurHash) {
// Simply asserts that two trials using one-time randomization
// that have different names, normally generate different results.
//
// Note that depending on the one-time random initialization, they
// _might_ actually give the same result, but we know that given
// the particular low_entropy_source we use for unit tests they won't.
NormalizedMurmurHashEntropyProvider entropy_provider(
{1234, kMaxLowEntropySize});
auto trials = std::to_array<scoped_refptr<base::FieldTrial>>({
base::FieldTrialList::FactoryGetFieldTrial("one", 100, "default",
entropy_provider),
base::FieldTrialList::FactoryGetFieldTrial("two", 100, "default",
entropy_provider),
});
for (const scoped_refptr<base::FieldTrial>& trial : trials) {
for (int j = 0; j < 100; ++j)
trial->AppendGroup(std::string(), 1);
}
// The trials are most likely to give different results since they have
// different names.
EXPECT_NE(trials[0]->group_name(), trials[1]->group_name());
}
TEST(EntropyProviderTest, UseOneTimeRandomizationWithCustomSeedSHA1) {
// Ensures that two trials with different names but the same custom seed used
// for one time randomization produce the same group assignments.
SHA1EntropyProvider entropy_provider("client_id");
const uint32_t kCustomSeed = 9001;
auto trials = std::to_array<scoped_refptr<base::FieldTrial>>({
base::FieldTrialList::FactoryGetFieldTrial("one", 100, "default",
entropy_provider, kCustomSeed),
base::FieldTrialList::FactoryGetFieldTrial("two", 100, "default",
entropy_provider, kCustomSeed),
});
for (const scoped_refptr<base::FieldTrial>& trial : trials) {
for (int j = 0; j < 100; ++j)
trial->AppendGroup(std::string(), 1);
}
// Normally, these trials should produce different groups, but if the same
// custom seed is used, they should produce the same group assignment.
EXPECT_EQ(trials[0]->group_name(), trials[1]->group_name());
}
TEST(EntropyProviderTest,
UseOneTimeRandomizationWithCustomSeedNormalizedMurmurHash) {
// Ensures that two trials with different names but the same custom seed used
// for one time randomization produce the same group assignments.
NormalizedMurmurHashEntropyProvider entropy_provider(
{1234, kMaxLowEntropySize});
const uint32_t kCustomSeed = 9001;
auto trials = std::to_array<scoped_refptr<base::FieldTrial>>({
base::FieldTrialList::FactoryGetFieldTrial("one", 100, "default",
entropy_provider, kCustomSeed),
base::FieldTrialList::FactoryGetFieldTrial("two", 100, "default",
entropy_provider, kCustomSeed),
});
for (const scoped_refptr<base::FieldTrial>& trial : trials) {
for (int j = 0; j < 100; ++j)
trial->AppendGroup(std::string(), 1);
}
// Normally, these trials should produce different groups, but if the same
// custom seed is used, they should produce the same group assignment.
EXPECT_EQ(trials[0]->group_name(), trials[1]->group_name());
}
TEST(EntropyProviderTest, SHA1Entropy) {
const auto results = std::to_array<double>(
{GenerateSHA1Entropy("hi", "1"), GenerateSHA1Entropy("there", "1")});
EXPECT_NE(results[0], results[1]);
for (double result : results) {
EXPECT_LE(0.0, result);
EXPECT_GT(1.0, result);
}
EXPECT_EQ(GenerateSHA1Entropy("yo", "1"),
GenerateSHA1Entropy("yo", "1"));
EXPECT_NE(GenerateSHA1Entropy("yo", "something"),
GenerateSHA1Entropy("yo", "else"));
}
TEST(EntropyProviderTest, NormalizedMurmurHashEntropy) {
const auto results = std::to_array<double>(
{GenerateNormalizedMurmurHashEntropy({1234, kMaxLowEntropySize}, "1"),
GenerateNormalizedMurmurHashEntropy({4321, kMaxLowEntropySize}, "1")});
EXPECT_NE(results[0], results[1]);
for (double result : results) {
EXPECT_LE(0.0, result);
EXPECT_GT(1.0, result);
}
EXPECT_EQ(
GenerateNormalizedMurmurHashEntropy({1234, kMaxLowEntropySize}, "1"),
GenerateNormalizedMurmurHashEntropy({1234, kMaxLowEntropySize}, "1"));
EXPECT_NE(
GenerateNormalizedMurmurHashEntropy({1234, kMaxLowEntropySize},
"something"),
GenerateNormalizedMurmurHashEntropy({1234, kMaxLowEntropySize}, "else"));
}
TEST(EntropyProviderTest, NormalizedMurmurHashEntropyProviderResults) {
// Verifies that NormalizedMurmurHashEntropyProvider produces expected
// results. This ensures that the results are the same between platforms and
// ensures that changes to the implementation do not regress this
// accidentally.
EXPECT_DOUBLE_EQ(
1612 / static_cast<double>(kMaxLowEntropySize),
GenerateNormalizedMurmurHashEntropy({1234, kMaxLowEntropySize}, "XYZ"));
EXPECT_DOUBLE_EQ(
7066 / static_cast<double>(kMaxLowEntropySize),
GenerateNormalizedMurmurHashEntropy({1, kMaxLowEntropySize}, "Test"));
EXPECT_DOUBLE_EQ(
5668 / static_cast<double>(kMaxLowEntropySize),
GenerateNormalizedMurmurHashEntropy({5000, kMaxLowEntropySize}, "Foo"));
}
TEST(EntropyProviderTest, SHA1EntropyIsUniform) {
for (const char* name : kTestTrialNames) {
SHA1EntropyGenerator entropy_generator(name);
PerformEntropyUniformityTest(name, entropy_generator);
}
}
TEST(EntropyProviderTest, NormalizedMurmurHashEntropyIsUniform) {
for (const char* name : kTestTrialNames) {
NormalizedMurmurHashEntropyGenerator entropy_generator(name);
PerformEntropyUniformityTest(name, entropy_generator);
}
}
TEST(EntropyProviderTest, InstantiationWithLimitedEntropyRandomizationSource) {
const EntropyProviders entropy_providers(
"client_id", {0, 8000}, "limited_entropy_randomization_source");
EXPECT_TRUE(entropy_providers.has_limited_entropy());
}
TEST(EntropyProviderTest,
InstantiationWithLimitedEntropyRandomizationSourceAsEmptyString) {
const EntropyProviders without_limited_entropy_randomization_source(
"client_id", {0, 8000},
/*limited_entropy_randomization_source=*/std::string_view());
EXPECT_FALSE(
without_limited_entropy_randomization_source.has_limited_entropy());
}
} // namespace variations
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