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/*
* Copyright (C) 2015 Apple Inc. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* 1. Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* 2. Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
*
* THIS SOFTWARE IS PROVIDED BY APPLE INC. AND ITS CONTRIBUTORS ``AS IS''
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO,
* THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL APPLE INC. OR ITS CONTRIBUTORS
* BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
* CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
* SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
* CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
* ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
* THE POSSIBILITY OF SUCH DAMAGE.
*/
#include "config.h"
#include <wtf/BloomFilter.h>
#include <wtf/RandomNumber.h>
#include <wtf/SHA1.h>
namespace TestWebKitAPI {
static Vector<unsigned> generateRandomHashes(size_t hashCount)
{
Vector<unsigned> hashes;
for (unsigned i = 0; i < hashCount; ++i)
hashes.append(static_cast<unsigned>(randomNumber() * std::numeric_limits<unsigned>::max()));
return hashes;
}
static Vector<SHA1::Digest> generateRandomDigests(size_t hashCount)
{
Vector<SHA1::Digest> hashes;
SHA1 sha1;
for (unsigned i = 0; i < hashCount; ++i) {
double random = randomNumber();
sha1.addBytes(reinterpret_cast<uint8_t*>(&random), sizeof(double));
SHA1::Digest digest;
sha1.computeHash(digest);
hashes.append(digest);
}
return hashes;
}
TEST(WTF_BloomFilter, Basic)
{
const unsigned hashCount = 1000;
auto hashes = generateRandomHashes(hashCount);
BloomFilter<16> filter;
for (auto hash : hashes)
filter.add(hash);
for (auto hash : hashes)
EXPECT_TRUE(filter.mayContain(hash));
auto moreHashes = generateRandomHashes(hashCount);
unsigned mayContainCount = 0;
for (auto hash : moreHashes)
mayContainCount += filter.mayContain(hash) ? 1 : 0;
// False positive rate is ~0.09% so this should always be true.
EXPECT_TRUE(mayContainCount < hashCount / 10);
for (auto hash : moreHashes)
filter.add(hash);
for (auto hash : hashes)
EXPECT_TRUE(filter.mayContain(hash));
for (auto hash : moreHashes)
EXPECT_TRUE(filter.mayContain(hash));
}
TEST(WTF_BloomFilter, BasicDigest)
{
const unsigned hashCount = 1000;
auto hashes = generateRandomDigests(hashCount);
BloomFilter<20> filter;
for (auto hash : hashes)
filter.add(hash);
for (auto hash : hashes)
EXPECT_TRUE(filter.mayContain(hash));
auto moreHashes = generateRandomDigests(hashCount);
unsigned mayContainCount = 0;
for (auto hash : moreHashes)
mayContainCount += filter.mayContain(hash) ? 1 : 0;
// False positive rate is ~0.000004% so this should always be true.
EXPECT_TRUE(mayContainCount < hashCount / 10);
for (auto hash : moreHashes)
filter.add(hash);
for (auto hash : hashes)
EXPECT_TRUE(filter.mayContain(hash));
for (auto hash : moreHashes)
EXPECT_TRUE(filter.mayContain(hash));
}
TEST(WTF_BloomFilter, BasicCounting)
{
const unsigned hashCount = 1000;
auto hashes = generateRandomHashes(hashCount);
CountingBloomFilter<16> filter;
for (auto hash : hashes)
filter.add(hash);
for (auto hash : hashes)
EXPECT_TRUE(filter.mayContain(hash));
for (auto hash : hashes)
filter.add(hash);
for (auto hash : hashes)
EXPECT_TRUE(filter.mayContain(hash));
for (auto hash : hashes)
filter.remove(hash);
for (auto hash : hashes)
EXPECT_TRUE(filter.mayContain(hash));
auto moreHashes = generateRandomHashes(hashCount);
unsigned mayContainCount = 0;
for (auto hash : moreHashes)
mayContainCount += filter.mayContain(hash) ? 1 : 0;
// False positive rate is ~0.09% so this should always be true.
EXPECT_TRUE(mayContainCount < hashCount / 10);
for (auto hash : moreHashes)
filter.add(hash);
for (auto hash : hashes)
filter.remove(hash);
for (auto hash : moreHashes)
EXPECT_TRUE(filter.mayContain(hash));
for (auto hash : moreHashes)
filter.remove(hash);
for (auto hash : hashes)
EXPECT_TRUE(!filter.mayContain(hash));
for (auto hash : moreHashes)
EXPECT_TRUE(!filter.mayContain(hash));
}
TEST(WTF_BloomFilter, Clear)
{
const unsigned hashCount = 1000;
auto hashes = generateRandomHashes(hashCount);
BloomFilter<16> filter;
for (auto hash : hashes)
filter.add(hash);
filter.clear();
for (auto hash : hashes)
EXPECT_TRUE(!filter.mayContain(hash));
}
TEST(WTF_BloomFilter, ClearCounting)
{
const unsigned hashCount = 1000;
auto hashes = generateRandomHashes(hashCount);
CountingBloomFilter<16> filter;
for (auto hash : hashes)
filter.add(hash);
for (auto hash : hashes)
filter.add(hash);
filter.clear();
for (auto hash : hashes)
EXPECT_TRUE(!filter.mayContain(hash));
}
TEST(WTF_BloomFilter, CountingOverflow)
{
const unsigned hashCount = 1000;
auto hashes = generateRandomHashes(hashCount);
CountingBloomFilter<16> filter;
for (auto hash : hashes)
filter.add(hash);
for (unsigned i = 0; i < filter.maximumCount() + 100; ++i)
filter.add(hashes[0]);
for (auto hash : hashes)
EXPECT_TRUE(filter.mayContain(hash));
for (auto hash : hashes)
filter.remove(hash);
unsigned mayContainCount = 0;
for (auto hash : hashes) {
if (hash == hashes[0])
EXPECT_TRUE(filter.mayContain(hash));
else
mayContainCount += filter.mayContain(hash) ? 1 : 0;
}
// False positive rate should be very low.
EXPECT_TRUE(mayContainCount < hashCount / 100);
for (unsigned i = 0; i < filter.maximumCount() + 100; ++i)
filter.remove(hashes[0]);
// The bucket has overflowed and is stuck.
EXPECT_TRUE(filter.mayContain(hashes[0]));
}
TEST(WTF_BloomFilter, Combine)
{
const unsigned hashCount = 1000;
auto hashes = generateRandomHashes(hashCount);
BloomFilter<16> filter;
for (auto hash : hashes)
filter.add(hash);
auto moreHashes = generateRandomHashes(hashCount);
BloomFilter<16> anotherFilter;
for (auto hash : moreHashes)
anotherFilter.add(hash);
filter.add(anotherFilter);
for (auto hash : hashes)
EXPECT_TRUE(filter.mayContain(hash));
for (auto hash : moreHashes)
EXPECT_TRUE(filter.mayContain(hash));
}
}