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LibTest: Add the RandomRun abstraction
To be used later by generators and during shrinking. The generators used in randomized tests will record the drawn random bits into a RandomRun. This is a layer of indirection that will help us automatically shrink any generated value without any user input. (Having to provide manually defined shrinkers is a downside to many randomized / property-based testing libraries like QuickCheck for Haskell.)
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Userland/Libraries/LibTest/Randomized/RandomRun.h
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Userland/Libraries/LibTest/Randomized/RandomRun.h
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/*
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* Copyright (c) 2023, Martin Janiczek <martin@janiczek.cz>.
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*
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* SPDX-License-Identifier: BSD-2-Clause
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*/
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#pragma once
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#include <AK/QuickSort.h>
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#include <AK/Vector.h>
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#include <LibTest/Randomized/Chunk.h>
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namespace Test {
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namespace Randomized {
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// RandomRun is a record of random bits used in generation of random values.
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// Once a value failing user test is found, we then attempt to shrink its
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// RandomRun using various ShrinkCommands.
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//
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// This means that we construct new RandomRuns by saying "OK, but what if the
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// PRNG gave you 0 instead of 23 that time..." The runner then tries to
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// generate a new value from the new RandomRun; if it succeeds and the value
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// still fails the test, we've shrunk our counterexample some!
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//
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// RandomRun is conceptually a sequence of unsigned integers, e.g.
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// [5,3,10,8,0,0,1].
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class RandomRun {
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public:
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RandomRun() = default;
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RandomRun(RandomRun const& rhs) = default;
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RandomRun& operator=(RandomRun const& rhs) = default;
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explicit RandomRun(Vector<u32> const& data)
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: m_data(move(data))
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{
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}
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bool is_empty() const { return m_data.is_empty(); }
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bool contains_chunk(Chunk const& c) const { return c.index + c.size <= m_data.size(); }
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void append(u32 n) { m_data.append(n); }
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size_t size() const { return m_data.size(); }
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Optional<u32> next()
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{
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if (m_current_index < m_data.size()) {
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return m_data[m_current_index++];
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}
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return Optional<u32> {};
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}
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u32& operator[](size_t index) { return m_data[index]; }
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u32 const& operator[](size_t index) const { return m_data[index]; }
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Vector<u32> data() const { return m_data; }
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// Shortlex sorting
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//
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// This is the metric by which we try to minimize (shrink) the sequence of
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// random choices, from which we later generate values.
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//
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// Shorter is better; if the length is equal then lexicographic order is
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// used. See [paper], section 2.2.
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//
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// Examples:
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// [9,9,9] < [0,0,0,0] (shorter is better)
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// [8,9,9] < [9,0,0] (lexicographic ordering: numbers that appear earlier
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// are more "important" than numbers that follow them)
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//
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// [paper]: https://drops.dagstuhl.de/opus/volltexte/2020/13170/
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bool is_shortlex_smaller_than(RandomRun const& rhs) const
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{
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auto lhs_size = size();
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auto rhs_size = rhs.size();
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if (lhs_size < rhs_size)
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return true;
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if (lhs_size > rhs_size)
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return false;
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for (size_t i = 0; i < lhs_size; i++) {
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if (m_data[i] < rhs.m_data[i])
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return true;
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if (m_data[i] > rhs.m_data[i])
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return false;
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}
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return false;
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}
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RandomRun with_sorted(Chunk c) const
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{
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Vector<u32> new_data = m_data;
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AK::dual_pivot_quick_sort(
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new_data,
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c.index,
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c.index + c.size - 1,
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[](auto& a, auto& b) { return a < b; });
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return RandomRun(move(new_data));
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}
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RandomRun with_deleted(Chunk c) const
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{
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Vector<u32> new_data(m_data);
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new_data.remove(c.index, c.size);
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return RandomRun(move(new_data));
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}
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private:
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Vector<u32> m_data;
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size_t m_current_index = 0;
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};
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} // namespace Randomized
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} // namespace Test
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template<>
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struct AK::Formatter<Test::Randomized::RandomRun> : Formatter<StringView> {
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ErrorOr<void> format(FormatBuilder& builder, Test::Randomized::RandomRun run)
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{
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return Formatter<StringView>::format(builder, TRY(String::formatted("[{}]"sv, TRY(String::join(',', run.data(), "{}"sv)))));
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}
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};
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