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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 "base/metrics/histogram_base.h"
#include <limits>
#include <string_view>
#include <vector>
#include "base/metrics/histogram.h"
#include "base/metrics/sample_vector.h"
#include "base/metrics/sparse_histogram.h"
#include "base/metrics/statistics_recorder.h"
#include "base/pickle.h"
#include "testing/gtest/include/gtest/gtest.h"
namespace base {
class HistogramBaseTest : public testing::Test {
public:
HistogramBaseTest() {
// Each test will have a clean state (no Histogram / BucketRanges
// registered).
ResetStatisticsRecorder();
}
HistogramBaseTest(const HistogramBaseTest&) = delete;
HistogramBaseTest& operator=(const HistogramBaseTest&) = delete;
~HistogramBaseTest() override = default;
protected:
void ResetStatisticsRecorder() {
// It is necessary to fully destruct any existing StatisticsRecorder
// before creating a new one.
statistics_recorder_.reset();
statistics_recorder_ = StatisticsRecorder::CreateTemporaryForTesting();
}
private:
std::unique_ptr<StatisticsRecorder> statistics_recorder_;
};
TEST_F(HistogramBaseTest, DeserializeHistogram) {
HistogramBase* histogram =
Histogram::FactoryGet("TestHistogram", 1, 1000, 10,
(HistogramBase::kUmaTargetedHistogramFlag |
HistogramBase::kIPCSerializationSourceFlag));
Pickle pickle;
histogram->SerializeInfo(&pickle);
PickleIterator iter(pickle);
HistogramBase* deserialized = DeserializeHistogramInfo(&iter);
EXPECT_EQ(histogram, deserialized);
ResetStatisticsRecorder();
PickleIterator iter2(pickle);
deserialized = DeserializeHistogramInfo(&iter2);
EXPECT_TRUE(deserialized);
EXPECT_NE(histogram, deserialized);
EXPECT_EQ("TestHistogram", deserialized->histogram_name());
EXPECT_TRUE(deserialized->HasConstructionArguments(1, 1000, 10));
// kIPCSerializationSourceFlag will be cleared.
EXPECT_EQ(HistogramBase::kUmaTargetedHistogramFlag, deserialized->flags());
}
TEST_F(HistogramBaseTest, DeserializeLinearHistogram) {
HistogramBase* histogram = LinearHistogram::FactoryGet(
"TestHistogram", 1, 1000, 10, HistogramBase::kIPCSerializationSourceFlag);
Pickle pickle;
histogram->SerializeInfo(&pickle);
PickleIterator iter(pickle);
HistogramBase* deserialized = DeserializeHistogramInfo(&iter);
EXPECT_EQ(histogram, deserialized);
ResetStatisticsRecorder();
PickleIterator iter2(pickle);
deserialized = DeserializeHistogramInfo(&iter2);
EXPECT_TRUE(deserialized);
EXPECT_NE(histogram, deserialized);
EXPECT_EQ("TestHistogram", deserialized->histogram_name());
EXPECT_TRUE(deserialized->HasConstructionArguments(1, 1000, 10));
EXPECT_EQ(0, deserialized->flags());
}
TEST_F(HistogramBaseTest, DeserializeBooleanHistogram) {
HistogramBase* histogram = BooleanHistogram::FactoryGet(
"TestHistogram", HistogramBase::kIPCSerializationSourceFlag);
Pickle pickle;
histogram->SerializeInfo(&pickle);
PickleIterator iter(pickle);
HistogramBase* deserialized = DeserializeHistogramInfo(&iter);
EXPECT_EQ(histogram, deserialized);
ResetStatisticsRecorder();
PickleIterator iter2(pickle);
deserialized = DeserializeHistogramInfo(&iter2);
EXPECT_TRUE(deserialized);
EXPECT_NE(histogram, deserialized);
EXPECT_EQ("TestHistogram", deserialized->histogram_name());
EXPECT_TRUE(deserialized->HasConstructionArguments(1, 2, 3));
EXPECT_EQ(0, deserialized->flags());
}
TEST_F(HistogramBaseTest, DeserializeCustomHistogram) {
std::vector<HistogramBase::Sample32> ranges;
ranges.push_back(13);
ranges.push_back(5);
ranges.push_back(9);
HistogramBase* histogram = CustomHistogram::FactoryGet(
"TestHistogram", ranges, HistogramBase::kIPCSerializationSourceFlag);
Pickle pickle;
histogram->SerializeInfo(&pickle);
PickleIterator iter(pickle);
HistogramBase* deserialized = DeserializeHistogramInfo(&iter);
EXPECT_EQ(histogram, deserialized);
ResetStatisticsRecorder();
PickleIterator iter2(pickle);
deserialized = DeserializeHistogramInfo(&iter2);
EXPECT_TRUE(deserialized);
EXPECT_NE(histogram, deserialized);
EXPECT_EQ("TestHistogram", deserialized->histogram_name());
EXPECT_TRUE(deserialized->HasConstructionArguments(5, 13, 4));
EXPECT_EQ(0, deserialized->flags());
}
TEST_F(HistogramBaseTest, DeserializeSparseHistogram) {
HistogramBase* histogram = SparseHistogram::FactoryGet(
"TestHistogram", HistogramBase::kIPCSerializationSourceFlag);
Pickle pickle;
histogram->SerializeInfo(&pickle);
PickleIterator iter(pickle);
HistogramBase* deserialized = DeserializeHistogramInfo(&iter);
EXPECT_EQ(histogram, deserialized);
ResetStatisticsRecorder();
PickleIterator iter2(pickle);
deserialized = DeserializeHistogramInfo(&iter2);
EXPECT_TRUE(deserialized);
EXPECT_NE(histogram, deserialized);
EXPECT_EQ("TestHistogram", deserialized->histogram_name());
EXPECT_EQ(0, deserialized->flags());
}
TEST_F(HistogramBaseTest, AddKilo) {
HistogramBase* histogram =
LinearHistogram::FactoryGet("TestAddKiloHistogram", 1, 1000, 100, 0);
histogram->AddKilo(100, 1000);
histogram->AddKilo(200, 2000);
histogram->AddKilo(300, 1500);
std::unique_ptr<HistogramSamples> samples = histogram->SnapshotSamples();
EXPECT_EQ(1, samples->GetCount(100));
EXPECT_EQ(2, samples->GetCount(200));
EXPECT_LE(1, samples->GetCount(300));
EXPECT_GE(2, samples->GetCount(300));
}
TEST_F(HistogramBaseTest, AddKiB) {
HistogramBase* histogram =
LinearHistogram::FactoryGet("TestAddKiBHistogram", 1, 1000, 100, 0);
histogram->AddKiB(100, 1024);
histogram->AddKiB(200, 2048);
histogram->AddKiB(300, 1536);
std::unique_ptr<HistogramSamples> samples = histogram->SnapshotSamples();
EXPECT_EQ(1, samples->GetCount(100));
EXPECT_EQ(2, samples->GetCount(200));
EXPECT_LE(1, samples->GetCount(300));
EXPECT_GE(2, samples->GetCount(300));
}
TEST_F(HistogramBaseTest, AddTimeMillisecondsGranularityOverflow) {
const HistogramBase::Sample32 sample_max =
std::numeric_limits<HistogramBase::Sample32>::max() / 2;
HistogramBase* histogram = LinearHistogram::FactoryGet(
"TestAddTimeMillisecondsGranularity1", 1, sample_max, 100, 0);
int64_t large_positive = std::numeric_limits<int64_t>::max();
// |add_count| is the number of large values that have been added to the
// histogram. We consider a number to be 'large' if it cannot be represented
// in a HistogramBase::Sample32.
int add_count = 0;
while (large_positive > std::numeric_limits<HistogramBase::Sample32>::max()) {
// Add the TimeDelta corresponding to |large_positive| milliseconds to the
// histogram.
histogram->AddTimeMillisecondsGranularity(Milliseconds(large_positive));
++add_count;
// Reduce the value of |large_positive|. The choice of 7 here is
// arbitrary.
large_positive /= 7;
}
std::unique_ptr<HistogramSamples> samples = histogram->SnapshotSamples();
// All of the reported values must have gone into the max overflow bucket.
EXPECT_EQ(add_count, samples->GetCount(sample_max));
// We now perform the analoguous operations, now with negative values with a
// large absolute value.
histogram = LinearHistogram::FactoryGet("TestAddTimeMillisecondsGranularity2",
1, sample_max, 100, 0);
int64_t large_negative = std::numeric_limits<int64_t>::min();
add_count = 0;
while (large_negative < std::numeric_limits<HistogramBase::Sample32>::min()) {
histogram->AddTimeMillisecondsGranularity(Milliseconds(large_negative));
++add_count;
large_negative /= 7;
}
samples = histogram->SnapshotSamples();
// All of the reported values must have gone into the min overflow bucket.
EXPECT_EQ(add_count, samples->GetCount(0));
}
TEST_F(HistogramBaseTest, AddTimeMicrosecondsGranularityOverflow) {
// Nothing to test if we don't have a high resolution clock.
if (!TimeTicks::IsHighResolution()) {
return;
}
const HistogramBase::Sample32 sample_max =
std::numeric_limits<HistogramBase::Sample32>::max() / 2;
HistogramBase* histogram = LinearHistogram::FactoryGet(
"TestAddTimeMicrosecondsGranularity1", 1, sample_max, 100, 0);
int64_t large_positive = std::numeric_limits<int64_t>::max();
// |add_count| is the number of large values that have been added to the
// histogram. We consider a number to be 'large' if it cannot be represented
// in a HistogramBase::Sample32.
int add_count = 0;
while (large_positive > std::numeric_limits<HistogramBase::Sample32>::max()) {
// Add the TimeDelta corresponding to |large_positive| microseconds to the
// histogram.
histogram->AddTimeMicrosecondsGranularity(Microseconds(large_positive));
++add_count;
// Reduce the value of |large_positive|. The choice of 7 here is
// arbitrary.
large_positive /= 7;
}
std::unique_ptr<HistogramSamples> samples = histogram->SnapshotSamples();
// All of the reported values must have gone into the max overflow bucket.
EXPECT_EQ(add_count, samples->GetCount(sample_max));
// We now perform the analoguous operations, now with negative values with a
// large absolute value.
histogram = LinearHistogram::FactoryGet("TestAddTimeMicrosecondsGranularity2",
1, sample_max, 100, 0);
int64_t large_negative = std::numeric_limits<int64_t>::min();
add_count = 0;
while (large_negative < std::numeric_limits<HistogramBase::Sample32>::min()) {
histogram->AddTimeMicrosecondsGranularity(Microseconds(large_negative));
++add_count;
large_negative /= 7;
}
samples = histogram->SnapshotSamples();
// All of the reported values must have gone into the min overflow bucket.
EXPECT_EQ(add_count, samples->GetCount(0));
}
} // namespace base
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