solidity/test/yulPhaser/Mutations.cpp

/*
	This file is part of solidity.

	solidity is free software: you can redistribute it and/or modify
	it under the terms of the GNU General Public License as published by
	the Free Software Foundation, either version 3 of the License, or
	(at your option) any later version.

	solidity is distributed in the hope that it will be useful,
	but WITHOUT ANY WARRANTY; without even the implied warranty of
	MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
	GNU General Public License for more details.

	You should have received a copy of the GNU General Public License
	along with solidity.  If not, see <http://www.gnu.org/licenses/>.
*/
// SPDX-License-Identifier: GPL-3.0

#include <test/yulPhaser/TestHelpers.h>

#include <tools/yulPhaser/Mutations.h>
#include <tools/yulPhaser/SimulationRNG.h>

#include <libsolutil/CommonIO.h>
#include <libyul/optimiser/Suite.h>

#include <boost/test/unit_test.hpp>
#include <boost/algorithm/string/predicate.hpp>

#include <algorithm>
#include <vector>

using namespace std;
using namespace solidity::util;
using namespace solidity::yul;

namespace solidity::phaser::test
{

BOOST_AUTO_TEST_SUITE(Phaser, *boost::unit_test::label("nooptions"))
BOOST_AUTO_TEST_SUITE(MutationsTest)
BOOST_AUTO_TEST_SUITE(GeneRandomisationTest)

BOOST_AUTO_TEST_CASE(geneRandomisation_should_iterate_over_genes_and_replace_them_with_random_ones_with_given_probability)
{
	size_t constexpr inputLength = 1000;
	double constexpr tolerance = 0.05;

	// Use genes that do not represent valid step abbreviations to be able to easily spot added steps.
	assert(OptimiserSuite::stepAbbreviationToNameMap().count('.') == 0);
	Chromosome input = Chromosome(string(inputLength, '.'));

	SimulationRNG::reset(1);
	for (size_t randomisationChancePercent = 20; randomisationChancePercent <= 100; randomisationChancePercent += 20)
	{
		double const randomisationChance = double(randomisationChancePercent) / 100.0;

		Chromosome output = geneRandomisation(randomisationChance)(input);
		string outputGenes = output.genes();
		BOOST_REQUIRE(output.length() == input.length());

		double const expectedValue = randomisationChance;
		double const variance = randomisationChance * (1 - randomisationChance);
		double const randomisedGeneCount = double(input.length() - static_cast<size_t>(count(outputGenes.begin(), outputGenes.end(), '.')));
		double const squaredError =
			(inputLength - randomisedGeneCount) * expectedValue * expectedValue +
			randomisedGeneCount * (1 - expectedValue) * (1 - expectedValue);

		BOOST_TEST(abs(randomisedGeneCount / inputLength - expectedValue) < tolerance);
		BOOST_TEST(abs(squaredError / inputLength - variance) < tolerance);
	}
}

BOOST_AUTO_TEST_CASE(geneRandomisation_should_return_identical_chromosome_if_probability_is_zero)
{
	Chromosome chromosome("fcCUnDvejsrmV");
	function<Mutation> mutation = geneRandomisation(0.0);

	BOOST_TEST(mutation(chromosome) == chromosome);
}

BOOST_AUTO_TEST_CASE(geneDeletion_should_iterate_over_genes_and_delete_them_with_given_probability)
{
	size_t constexpr inputLength = 1000;
	double constexpr tolerance = 0.05;

	// Use genes that do not represent valid step abbreviations to be able to easily spot added steps.
	assert(OptimiserSuite::stepAbbreviationToNameMap().count('.') == 0);
	Chromosome input = Chromosome(string(inputLength, '.'));

	SimulationRNG::reset(1);
	for (size_t deletionChancePercent = 20; deletionChancePercent < 100; deletionChancePercent += 20)
	{
		double const deletionChance = double(deletionChancePercent) / 100.0;

		Chromosome output = geneDeletion(deletionChance)(input);
		string outputGenes = output.genes();
		BOOST_REQUIRE(output.length() <= input.length());
		BOOST_REQUIRE(static_cast<size_t>(count(outputGenes.begin(), outputGenes.end(), '.')) == output.length());

		double const expectedValue = deletionChance;
		double const variance = deletionChance * (1.0 - deletionChance);
		double const deletedGeneCount = double(input.length() - output.length());
		double const squaredError =
			(double(inputLength) - deletedGeneCount) * expectedValue * expectedValue +
			deletedGeneCount * (1.0 - expectedValue) * (1.0 - expectedValue);

		BOOST_TEST(abs(deletedGeneCount / double(inputLength) - expectedValue) < tolerance);
		BOOST_TEST(abs(squaredError / double(inputLength) - variance) < tolerance);
	}
}

BOOST_AUTO_TEST_CASE(geneDeletion_should_return_identical_chromosome_if_probability_is_zero)
{
	Chromosome chromosome("fcCUnDvejsrmV");
	function<Mutation> mutation = geneDeletion(0.0);

	BOOST_TEST(mutation(chromosome) == chromosome);
}

BOOST_AUTO_TEST_CASE(geneDeletion_should_delete_all_genes_if_probability_is_one)
{
	Chromosome chromosome("fcCUnDvejsrmV");
	function<Mutation> mutation = geneDeletion(1.0);

	BOOST_TEST(mutation(chromosome) == Chromosome(""));
}

BOOST_AUTO_TEST_CASE(geneAddition_should_iterate_over_gene_positions_and_insert_new_genes_with_given_probability)
{
	size_t constexpr inputLength = 1000;
	double constexpr tolerance = 0.05;
	size_t constexpr maxAdditions = inputLength + 1;

	// Use genes that do not represent valid step abbreviations to be able to easily spot added steps.
	assert(OptimiserSuite::stepAbbreviationToNameMap().count('.') == 0);
	Chromosome input = Chromosome(string(inputLength, '.'));

	SimulationRNG::reset(1);
	for (size_t additionChancePercent = 20; additionChancePercent < 100; additionChancePercent += 20)
	{
		double const additionChance = double(additionChancePercent) / 100.0;

		Chromosome output = geneAddition(additionChance)(input);
		BOOST_REQUIRE(output.length() >= input.length());
		BOOST_REQUIRE(output.length() <= inputLength + maxAdditions);

		string_view outputGenes = output.genes();
		size_t preservedGeneCount = static_cast<size_t>(count(outputGenes.begin(), outputGenes.end(), '.'));
		BOOST_REQUIRE(preservedGeneCount == input.length());

		double const expectedValue = additionChance;
		double const variance = additionChance * (1.0 - additionChance);
		double const addedGeneCount = double(output.length() - preservedGeneCount);
		double const squaredError =
			(double(maxAdditions) - addedGeneCount) * expectedValue * expectedValue +
			addedGeneCount * (1.0 - expectedValue) * (1.0 - expectedValue);

		BOOST_TEST(abs(addedGeneCount / double(maxAdditions) - expectedValue) < tolerance);
		BOOST_TEST(abs(squaredError / double(maxAdditions) - variance) < tolerance);
	}
}

BOOST_AUTO_TEST_CASE(geneAddition_should_be_able_to_insert_before_first_position)
{
	SimulationRNG::reset(7);
	Chromosome chromosome("fcCUnDvejs");
	function<Mutation> mutation = geneAddition(0.1);

	Chromosome mutatedChromosome = mutation(chromosome);
	BOOST_TEST(mutatedChromosome.length() > chromosome.length());
	BOOST_TEST(boost::ends_with(mutatedChromosome.genes(), chromosome.genes()));
}

BOOST_AUTO_TEST_CASE(geneAddition_should_be_able_to_insert_after_last_position)
{
	SimulationRNG::reset(81);
	Chromosome chromosome("fcCUnDvejs");
	function<Mutation> mutation = geneAddition(0.1);

	Chromosome mutatedChromosome = mutation(chromosome);
	BOOST_TEST(mutatedChromosome.length() > chromosome.length());
	BOOST_TEST(boost::starts_with(mutatedChromosome.genes(), chromosome.genes()));
}

BOOST_AUTO_TEST_CASE(geneAddition_should_return_identical_chromosome_if_probability_is_zero)
{
	Chromosome chromosome("fcCUnDvejsrmV");
	function<Mutation> mutation = geneAddition(0.0);

	BOOST_TEST(mutation(chromosome) == chromosome);
}

BOOST_AUTO_TEST_CASE(geneAddition_should_insert_genes_at_all_positions_if_probability_is_one)
{
	Chromosome chromosome("fcCUnDvejsrmV");
	function<Mutation> mutation = geneAddition(1.0);

	Chromosome mutatedChromosome = mutation(chromosome);
	BOOST_TEST(mutatedChromosome.length() == chromosome.length() * 2 + 1);

	vector<string> originalGenes;
	for (size_t i = 0; i < mutatedChromosome.length() - 1; ++i)
		if (i % 2 == 1)
			originalGenes.push_back(mutatedChromosome.optimisationSteps()[i]);

	BOOST_TEST(Chromosome(originalGenes) == chromosome);
}

BOOST_AUTO_TEST_CASE(alternativeMutations_should_choose_between_mutations_with_given_probability)
{
	SimulationRNG::reset(1);
	Chromosome chromosome("a");
	function<Mutation> mutation = alternativeMutations(
		0.8,
		wholeChromosomeReplacement(Chromosome("c")),
		wholeChromosomeReplacement(Chromosome("f"))
	);

	size_t cCount = 0;
	size_t fCount = 0;
	for (size_t i = 0; i < 10; ++i)
	{
		Chromosome mutatedChromosome = mutation(chromosome);
		cCount += (mutatedChromosome == Chromosome("c") ? 1u : 0u);
		fCount += (mutatedChromosome == Chromosome("f") ? 1u : 0u);
	}

	// This particular seed results in 7 "c"s out of 10 which looks plausible given the 80% chance.
	BOOST_TEST(cCount == 7);
	BOOST_TEST(fCount == 3);
}

BOOST_AUTO_TEST_CASE(alternativeMutations_should_always_choose_first_mutation_if_probability_is_one)
{
	Chromosome chromosome("a");
	function<Mutation> mutation = alternativeMutations(
		1.0,
		wholeChromosomeReplacement(Chromosome("c")),
		wholeChromosomeReplacement(Chromosome("f"))
	);

	for (size_t i = 0; i < 10; ++i)
		BOOST_TEST(mutation(chromosome) == Chromosome("c"));
}

BOOST_AUTO_TEST_CASE(alternativeMutations_should_always_choose_second_mutation_if_probability_is_zero)
{
	Chromosome chromosome("a");
	function<Mutation> mutation = alternativeMutations(
		0.0,
		wholeChromosomeReplacement(Chromosome("c")),
		wholeChromosomeReplacement(Chromosome("f"))
	);

	for (size_t i = 0; i < 10; ++i)
		BOOST_TEST(mutation(chromosome) == Chromosome("f"));
}

BOOST_AUTO_TEST_CASE(mutationSequence_should_apply_all_mutations)
{
	Chromosome chromosome("aaaaa");
	vector<string> steps = Chromosome::genesToSteps("gfc");
	function<Mutation> mutation = mutationSequence({
		geneSubstitution(3, steps[0]),
		geneSubstitution(2, steps[1]),
		geneSubstitution(1, steps[2]),
	});

	BOOST_TEST(mutation(chromosome) == Chromosome("acfga"));
}

BOOST_AUTO_TEST_CASE(mutationSequence_apply_mutations_in_the_order_they_are_given)
{
	Chromosome chromosome("aa");
	vector<string> steps = Chromosome::genesToSteps("gcfo");
	function<Mutation> mutation = mutationSequence({
		geneSubstitution(0, steps[0]),
		geneSubstitution(1, steps[1]),
		geneSubstitution(0, steps[2]),
		geneSubstitution(1, steps[3]),
	});

	BOOST_TEST(mutation(chromosome) == Chromosome("fo"));
}

BOOST_AUTO_TEST_CASE(mutationSequence_should_return_unmodified_chromosome_if_given_no_mutations)
{
	Chromosome chromosome("aa");
	function<Mutation> mutation = mutationSequence({});

	BOOST_TEST(mutation(chromosome) == chromosome);
}

BOOST_AUTO_TEST_CASE(randomPointCrossover_should_swap_chromosome_parts_at_random_point)
{
	function<Crossover> crossover = randomPointCrossover();

	SimulationRNG::reset(1);
	Chromosome result1 = crossover(Chromosome("aaaaaaaaaa"), Chromosome("cccccc"));
	BOOST_TEST(result1 == Chromosome("aaaccc"));

	SimulationRNG::reset(1);
	Chromosome result2 = crossover(Chromosome("cccccc"), Chromosome("aaaaaaaaaa"));
	BOOST_TEST(result2 == Chromosome("cccaaaaaaa"));
}

BOOST_AUTO_TEST_CASE(symmetricRandomPointCrossover_should_swap_chromosome_parts_at_random_point)
{
	function<SymmetricCrossover> crossover = symmetricRandomPointCrossover();

	SimulationRNG::reset(1);
	tuple<Chromosome, Chromosome> result1 = crossover(Chromosome("aaaaaaaaaa"), Chromosome("cccccc"));
	tuple<Chromosome, Chromosome> expectedPair1 = {Chromosome("aaaccc"), Chromosome("cccaaaaaaa")};
	BOOST_TEST(result1 == expectedPair1);

	tuple<Chromosome, Chromosome> result2 = crossover(Chromosome("cccccc"), Chromosome("aaaaaaaaaa"));
	tuple<Chromosome, Chromosome> expectedPair2 = {Chromosome("ccccccaaaa"), Chromosome("aaaaaa")};
	BOOST_TEST(result2 == expectedPair2);
}

BOOST_AUTO_TEST_CASE(randomPointCrossover_should_only_consider_points_available_on_both_chromosomes)
{
	SimulationRNG::reset(1);
	function<Crossover> crossover = randomPointCrossover();

	for (size_t i = 0; i < 30; ++i)
	{
		Chromosome result1 = crossover(Chromosome("aaa"), Chromosome("TTTTTTTTTTTTTTTTTTTT"));
		Chromosome result2 = crossover(Chromosome("TTTTTTTTTTTTTTTTTTTT"), Chromosome("aaa"));
		BOOST_TEST((
			result1 == Chromosome("TTTTTTTTTTTTTTTTTTTT") ||
			result1 == Chromosome("aTTTTTTTTTTTTTTTTTTT") ||
			result1 == Chromosome("aaTTTTTTTTTTTTTTTTTT") ||
			result1 == Chromosome("aaaTTTTTTTTTTTTTTTTT")
		));
		BOOST_TEST((
			result2 == Chromosome("aaa") ||
			result2 == Chromosome("Taa") ||
			result2 == Chromosome("TTa") ||
			result2 == Chromosome("TTT")
		));
	}
}

BOOST_AUTO_TEST_CASE(randomPointCrossover_should_never_split_at_position_zero_if_chromosomes_are_splittable)
{
	SimulationRNG::reset(1);
	function<Crossover> crossover = randomPointCrossover();

	for (size_t i = 0; i < 30; ++i)
	{
		Chromosome result1 = crossover(Chromosome("aa"), Chromosome("TTTTTTTTTTTTTTTTTTTT"));
		Chromosome result2 = crossover(Chromosome("TTTTTTTTTTTTTTTTTTTT"), Chromosome("aa"));
		BOOST_TEST(result1 != Chromosome("TTTTTTTTTTTTTTTTTTTT"));
		BOOST_TEST(result2 != Chromosome("aa"));
	}
}

BOOST_AUTO_TEST_CASE(randomPointCrossover_should_never_split_at_position_zero_if_chromosomes_are_not_empty)
{
	SimulationRNG::reset(1);
	function<Crossover> crossover = randomPointCrossover();

	for (size_t i = 0; i < 30; ++i)
	{
		Chromosome result1 = crossover(Chromosome("a"), Chromosome("T"));
		Chromosome result2 = crossover(Chromosome("T"), Chromosome("a"));
		BOOST_TEST(result1 == Chromosome("a"));
		BOOST_TEST(result2 == Chromosome("T"));
	}
}

BOOST_AUTO_TEST_CASE(randomPointCrossover_should_work_even_if_one_chromosome_is_unsplittable)
{
	function<Crossover> crossover = randomPointCrossover();

	SimulationRNG::reset(1);
	BOOST_CHECK(crossover(Chromosome("ff"), Chromosome("a")) == Chromosome("f"));
	BOOST_CHECK(crossover(Chromosome("a"), Chromosome("ff")) == Chromosome("af"));
}

BOOST_AUTO_TEST_CASE(randomPointCrossover_should_split_at_position_zero_only_if_at_least_one_chromosome_is_empty)
{
	Chromosome empty("");
	Chromosome unsplittable("a");
	Chromosome splittable("aaaa");
	function<Crossover> crossover = randomPointCrossover();

	SimulationRNG::reset(1);
	BOOST_CHECK(crossover(empty, empty) == empty);
	BOOST_CHECK(crossover(unsplittable, empty) == empty);
	BOOST_CHECK(crossover(empty, unsplittable) == unsplittable);
	BOOST_CHECK(crossover(splittable, empty) == empty);
	BOOST_CHECK(crossover(empty, splittable) == splittable);
}

BOOST_AUTO_TEST_CASE(fixedPointCrossover_should_swap_chromosome_parts_at_given_point)
{
	Chromosome result1 = fixedPointCrossover(0.8)(Chromosome("aaaaaaaaaa"), Chromosome("cccccccccc"));
	Chromosome result2 = fixedPointCrossover(0.8)(Chromosome("cccccccccc"), Chromosome("aaaaaaaaaa"));
	BOOST_TEST(result1 == Chromosome("aaaaaaaacc"));
	BOOST_TEST(result2 == Chromosome("ccccccccaa"));
}

BOOST_AUTO_TEST_CASE(fixedPointCrossover_should_determine_crossover_point_based_on_length_of_shorter_chromosome)
{
	Chromosome result1 = fixedPointCrossover(0.4)(Chromosome("aaaaa"), Chromosome("cccccccccc"));
	Chromosome result2 = fixedPointCrossover(0.4)(Chromosome("cccccccccc"), Chromosome("aaaaa"));
	BOOST_TEST(result1 == Chromosome("aacccccccc"));
	BOOST_TEST(result2 == Chromosome("ccaaa"));
}

BOOST_AUTO_TEST_CASE(fixedPointCrossover_should_round_split_point)
{
	Chromosome result1 = fixedPointCrossover(0.49)(Chromosome("aaaaa"), Chromosome("ccccc"));
	Chromosome result2 = fixedPointCrossover(0.49)(Chromosome("ccccc"), Chromosome("aaaaa"));
	BOOST_TEST(result1 == Chromosome("aaccc"));
	BOOST_TEST(result2 == Chromosome("ccaaa"));

	Chromosome result3 = fixedPointCrossover(0.50)(Chromosome("aaaaa"), Chromosome("ccccc"));
	Chromosome result4 = fixedPointCrossover(0.50)(Chromosome("ccccc"), Chromosome("aaaaa"));
	BOOST_TEST(result3 == Chromosome("aaacc"));
	BOOST_TEST(result4 == Chromosome("cccaa"));

	Chromosome result5 = fixedPointCrossover(0.51)(Chromosome("aaaaa"), Chromosome("ccccc"));
	Chromosome result6 = fixedPointCrossover(0.51)(Chromosome("ccccc"), Chromosome("aaaaa"));
	BOOST_TEST(result5 == Chromosome("aaacc"));
	BOOST_TEST(result6 == Chromosome("cccaa"));
}

BOOST_AUTO_TEST_CASE(fixedPointCrossover_should_split_at_position_zero_if_explicitly_requested)
{
	Chromosome result1 = fixedPointCrossover(0.0)(Chromosome("aaaaa"), Chromosome("cccccccccc"));
	Chromosome result2 = fixedPointCrossover(0.0)(Chromosome("cccccccccc"), Chromosome("aaaaa"));
	BOOST_TEST(result1 == Chromosome("cccccccccc"));
	BOOST_TEST(result2 == Chromosome("aaaaa"));
}

BOOST_AUTO_TEST_CASE(fixedPointCrossover_should_split_at_end_of_shorter_chromosome_if_crossover_point_is_after_last_position)
{
	Chromosome result1 = fixedPointCrossover(1.0)(Chromosome("aaaaa"), Chromosome("cccccccccc"));
	Chromosome result2 = fixedPointCrossover(1.0)(Chromosome("cccccccccc"), Chromosome("aaaaa"));
	BOOST_TEST(result1 == Chromosome("aaaaaccccc"));
	BOOST_TEST(result2 == Chromosome("ccccc"));
}

BOOST_AUTO_TEST_CASE(fixedPointCrossover_should_select_correct_split_point_for_unsplittable_chromosomes)
{
	function<Crossover> crossover00 = fixedPointCrossover(0.0);
	BOOST_CHECK(crossover00(Chromosome("fff"), Chromosome("a")) == Chromosome("a"));
	BOOST_CHECK(crossover00(Chromosome("a"), Chromosome("fff")) == Chromosome("fff"));

	BOOST_CHECK(crossover00(Chromosome("f"), Chromosome("a")) == Chromosome("a"));

	function<Crossover> crossover10 = fixedPointCrossover(1.0);
	BOOST_CHECK(crossover10(Chromosome("fff"), Chromosome("a")) == Chromosome("f"));
	BOOST_CHECK(crossover10(Chromosome("a"), Chromosome("fff")) == Chromosome("aff"));

	BOOST_CHECK(crossover10(Chromosome("f"), Chromosome("a")) == Chromosome("f"));
}

BOOST_AUTO_TEST_CASE(fixedPointCrossover_should_always_use_position_zero_as_split_point_when_chromosome_empty)
{
	Chromosome empty("");
	Chromosome unsplittable("f");
	Chromosome splittable("aaaa");

	function<Crossover> crossover00 = fixedPointCrossover(0.0);
	BOOST_CHECK(crossover00(empty, empty) == empty);
	BOOST_CHECK(crossover00(unsplittable, empty) == empty);
	BOOST_CHECK(crossover00(empty, unsplittable) == unsplittable);
	BOOST_CHECK(crossover00(splittable, empty) == empty);
	BOOST_CHECK(crossover00(empty, splittable) == splittable);

	function<Crossover> crossover10 = fixedPointCrossover(1.0);
	BOOST_CHECK(crossover10(empty, empty) == empty);
	BOOST_CHECK(crossover10(unsplittable, empty) == empty);
	BOOST_CHECK(crossover10(empty, unsplittable) == unsplittable);
	BOOST_CHECK(crossover10(splittable, empty) == empty);
	BOOST_CHECK(crossover10(empty, splittable) == splittable);
}

BOOST_AUTO_TEST_CASE(randomTwoPointCrossover_should_swap_chromosome_parts_between_two_random_points)
{
	function<Crossover> crossover = randomTwoPointCrossover();

	SimulationRNG::reset(1);
	Chromosome result1 = crossover(Chromosome("aaaaaaaaaa"), Chromosome("cccccc"));
	BOOST_TEST(result1 == Chromosome("aaacccaaaa"));

	SimulationRNG::reset(1);
	Chromosome result2 = crossover(Chromosome("cccccc"), Chromosome("aaaaaaaaaa"));
	BOOST_TEST(result2 == Chromosome("cccaaa"));
}

BOOST_AUTO_TEST_CASE(symmetricRandomTwoPointCrossover_should_swap_chromosome_parts_at_random_point)
{
	function<SymmetricCrossover> crossover = symmetricRandomTwoPointCrossover();

	SimulationRNG::reset(1);
	tuple<Chromosome, Chromosome> result1 = crossover(Chromosome("aaaaaaaaaa"), Chromosome("cccccc"));
	tuple<Chromosome, Chromosome> expectedPair1 = {Chromosome("aaacccaaaa"), Chromosome("cccaaa")};
	BOOST_TEST(result1 == expectedPair1);

	tuple<Chromosome, Chromosome> result2 = crossover(Chromosome("cccccc"), Chromosome("aaaaaaaaaa"));
	tuple<Chromosome, Chromosome> expectedPair2 = {Chromosome("ccccca"), Chromosome("aaaaacaaaa")};
	BOOST_TEST(result2 == expectedPair2);
}

BOOST_AUTO_TEST_CASE(randomTwoPointCrossover_should_only_consider_points_available_on_both_chromosomes)
{
	function<Crossover> crossover = randomTwoPointCrossover();

	for (size_t i = 0; i < 30; ++i)
	{
		Chromosome result1 = crossover(Chromosome("aaa"), Chromosome("TTTTTTTTTTTTTTTTTTTT"));
		Chromosome result2 = crossover(Chromosome("TTTTTTTTTTTTTTTTTTTT"), Chromosome("aaa"));
		BOOST_TEST((
			result1 == Chromosome("aaa") ||
			result1 == Chromosome("Taa") ||
			result1 == Chromosome("TTa") ||
			result1 == Chromosome("TTT") ||
			result1 == Chromosome("aTa") ||
			result1 == Chromosome("aTT") ||
			result1 == Chromosome("aaT")
		));
		BOOST_TEST((
			result2 == Chromosome("TTTTTTTTTTTTTTTTTTTT") ||
			result2 == Chromosome("aTTTTTTTTTTTTTTTTTTT") ||
			result2 == Chromosome("aaTTTTTTTTTTTTTTTTTT") ||
			result2 == Chromosome("aaaTTTTTTTTTTTTTTTTT") ||
			result2 == Chromosome("TaTTTTTTTTTTTTTTTTTT") ||
			result2 == Chromosome("TaaTTTTTTTTTTTTTTTTT") ||
			result2 == Chromosome("TTaTTTTTTTTTTTTTTTTT")
		));
	}
}

BOOST_AUTO_TEST_CASE(uniformCrossover_should_swap_randomly_selected_genes)
{
	function<Crossover> crossover = uniformCrossover(0.7);

	SimulationRNG::reset(1);
	Chromosome result1 = crossover(Chromosome("aaaaaaaaaa"), Chromosome("cccccc"));
	BOOST_TEST(result1 == Chromosome("caaacc"));

	SimulationRNG::reset(1);
	Chromosome result2 = crossover(Chromosome("cccccc"), Chromosome("aaaaaaaaaa"));
	BOOST_TEST(result2 == Chromosome("acccaaaaaa"));
}

BOOST_AUTO_TEST_CASE(symmetricUniformCrossover_should_swap_randomly_selected_genes)
{
	function<SymmetricCrossover> crossover = symmetricUniformCrossover(0.7);

	SimulationRNG::reset(1);
	tuple<Chromosome, Chromosome> result1 = crossover(Chromosome("aaaaaaaaaa"), Chromosome("cccccc"));
	tuple<Chromosome, Chromosome> expectedPair1 = {Chromosome("caaacc"), Chromosome("acccaaaaaa")};
	BOOST_TEST(result1 == expectedPair1);

	tuple<Chromosome, Chromosome> result2 = crossover(Chromosome("cccccc"), Chromosome("aaaaaaaaaa"));
	tuple<Chromosome, Chromosome> expectedPair2 = {Chromosome("caaaaaaaaa"), Chromosome("accccc")};
	BOOST_TEST(result2 == expectedPair2);
}

BOOST_AUTO_TEST_CASE(uniformCrossover_should_only_consider_points_available_on_both_chromosomes)
{
	function<Crossover> crossover = uniformCrossover(0.7);

	set<string> expectedPatterns = {
		"TTTTTTTTTTTTTTTTTTTT",
		"aTTTTTTTTTTTTTTTTTTT",
		"TaTTTTTTTTTTTTTTTTTT",
		"TTaTTTTTTTTTTTTTTTTT",
		"aaTTTTTTTTTTTTTTTTTT",
		"TaaTTTTTTTTTTTTTTTTT",
		"aTaTTTTTTTTTTTTTTTTT",
		"aaaTTTTTTTTTTTTTTTTT",
		"aaa",
		"Taa",
		"aTa",
		"aaT",
		"TTa",
		"aTT",
		"TaT",
		"TTT",
	};

	for (size_t i = 0; i < 30; ++i)
	{
		Chromosome result1 = crossover(Chromosome("aaa"), Chromosome("TTTTTTTTTTTTTTTTTTTT"));
		Chromosome result2 = crossover(Chromosome("TTTTTTTTTTTTTTTTTTTT"), Chromosome("aaa"));
		BOOST_TEST(expectedPatterns.count(toString(result1)) == 1);
		BOOST_TEST(expectedPatterns.count(toString(result2)) == 1);
	}
}

BOOST_AUTO_TEST_CASE(uniformCrossover_should_not_swap_anything_if_chance_is_zero)
{
	BOOST_TEST(uniformCrossover(0.0)(Chromosome("aaaaaaaaaa"), Chromosome("cccccc")) == Chromosome("aaaaaaaaaa"));
	BOOST_TEST(uniformCrossover(0.0)(Chromosome("cccccc"), Chromosome("aaaaaaaaaa")) == Chromosome("cccccc"));
}

BOOST_AUTO_TEST_CASE(uniformCrossover_should_swap_whole_chromosomes_if_chance_is_one)
{
	BOOST_TEST(uniformCrossover(1.0)(Chromosome("aaaaaaaaaa"), Chromosome("cccccc")) == Chromosome("cccccc"));
	BOOST_TEST(uniformCrossover(1.0)(Chromosome("cccccc"), Chromosome("aaaaaaaaaa")) == Chromosome("aaaaaaaaaa"));
}

BOOST_AUTO_TEST_CASE(uniformCrossover_should_swap_genes_with_uniform_probability)
{
	constexpr size_t operationCount = 1000;
	constexpr double swapChance = 0.8;
	constexpr double relativeTolerance = 0.05;
	double const expectedValue = swapChance;
	double const variance = swapChance * (1 - swapChance);

	function<Crossover> crossover = uniformCrossover(swapChance);
	Chromosome chromosome1("aaaaaaaaaa");
	Chromosome chromosome2("cccccccccc");

	vector<size_t> bernoulliTrials;
	for (size_t i = 0; i < operationCount; ++i)
	{
		string genes = toString(crossover(chromosome1, chromosome2));
		for (size_t j = 0; j < chromosome1.length(); ++j)
			bernoulliTrials.push_back(static_cast<size_t>(genes[j] == 'c'));
	}

	BOOST_TEST(abs(mean(bernoulliTrials) - expectedValue) < expectedValue * relativeTolerance);
	BOOST_TEST(abs(meanSquaredError(bernoulliTrials, expectedValue) - variance) < variance * relativeTolerance);
}

BOOST_AUTO_TEST_CASE(uniformCrossover_should_swap_tail_with_uniform_probability)
{
	constexpr size_t operationCount = 1000;
	constexpr double swapChance = 0.3;
	constexpr double relativeTolerance = 0.05;
	double const expectedValue = swapChance;
	double const variance = swapChance * (1 - swapChance);

	function<Crossover> crossover = uniformCrossover(swapChance);
	Chromosome chromosome1("aaaaa");
	Chromosome chromosome2("cccccccccc");

	vector<size_t> bernoulliTrials;
	for (size_t i = 0; i < operationCount; ++i)
	{
		string genes = toString(crossover(chromosome1, chromosome2));
		BOOST_REQUIRE(genes.size() == 5 || genes.size() == 10);
		bernoulliTrials.push_back(static_cast<size_t>(genes.size() == 10));
	}

	BOOST_TEST(abs(mean(bernoulliTrials) - expectedValue) < expectedValue * relativeTolerance);
	BOOST_TEST(abs(meanSquaredError(bernoulliTrials, expectedValue) - variance) < variance * relativeTolerance);
}

BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE_END()
BOOST_AUTO_TEST_SUITE_END()

}