blob: 949a0d93046b4ed5855d7d68b0b1c72340148d8b [file] [log] [blame] [edit]
// Copyright 2019 The Fuchsia Authors. All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.
#include <lib/affine/ratio.h>
#include <lib/affine/transform.h>
#include <stdint.h>
#include <fuzzer/FuzzedDataProvider.h>
using affine::Ratio;
using affine::Transform;
extern "C" int LLVMFuzzerTestOneInput(const uint8_t* data, size_t size) {
FuzzedDataProvider data_provider(data, size);
// Note: This intentionally skips trivial methods like Ratio::Inverse()
// Construct two Ratios
Ratio ratios[2];
for (auto i = 0; i < 2; i++) {
auto numerator = data_provider.ConsumeIntegral<uint32_t>();
// For denominators, we want to avoid expected errors for zero values
auto denominator = data_provider.ConsumeIntegralInRange<uint32_t>(1, UINT32_MAX);
ratios[i] = Ratio{numerator, denominator};
}
// Call Reduce() on copies, because it mutates in-place
Ratio(ratios[0].numerator(), ratios[0].denominator()).Reduce();
Ratio(ratios[1].numerator(), ratios[1].denominator()).Reduce();
// Product() defaults to Exact::Yes which would assert on loss of precision
Ratio::Product(ratios[0], ratios[1], Ratio::Exact::No);
Ratio::Product(ratios[1], ratios[0], Ratio::Exact::No);
// Exercise Ratio::Scale()
auto n = data_provider.ConsumeIntegral<int64_t>();
ratios[0] * n;
ratios[1] * n;
// Construct two Transforms
Transform transforms[2];
for (auto i = 0; i < 2; i++) {
auto a_offset = data_provider.ConsumeIntegral<int64_t>();
auto b_offset = data_provider.ConsumeIntegral<int64_t>();
transforms[i] = Transform{a_offset, b_offset, ratios[i]};
}
// We only use Apply() and not ApplyInverse() so we can avoid division by zero
transforms[0].Apply(n);
transforms[1].Apply(n);
// Compose() defaults to Exact::Yes which would assert on loss of precision
Transform::Compose(transforms[0], transforms[1], Ratio::Exact::No).Apply(n);
Transform::Compose(transforms[1], transforms[0], Ratio::Exact::No).Apply(n);
return 0;
}