org.evosuite.strategy.PropertiesTestGAFactory Maven / Gradle / Ivy
/**
* Copyright (C) 2010-2018 Gordon Fraser, Andrea Arcuri and EvoSuite
* contributors
*
* This file is part of EvoSuite.
*
* EvoSuite is free software: you can redistribute it and/or modify it
* under the terms of the GNU Lesser General Public License as published
* by the Free Software Foundation, either version 3.0 of the License, or
* (at your option) any later version.
*
* EvoSuite 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
* Lesser Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with EvoSuite. If not, see {
protected ChromosomeFactory getChromosomeFactory() {
switch (Properties.STRATEGY) {
case ONEBRANCH:
switch (Properties.TEST_FACTORY) {
case ALLMETHODS:
logger.info("Using all methods chromosome factory");
return new AllMethodsTestChromosomeFactory();
case RANDOM:
logger.info("Using random chromosome factory");
return new RandomLengthTestFactory();
case JUNIT:
logger.info("Using seeding chromosome factory");
return new JUnitTestCarvedChromosomeFactory(new RandomLengthTestFactory());
default:
}
case ENTBUG:
return new RandomLengthTestFactory();
default:
break;
}
throw new RuntimeException("Unsupported test factory: "
+ Properties.TEST_FACTORY);
}
private GeneticAlgorithm getGeneticAlgorithm(ChromosomeFactory factory) {
switch (Properties.ALGORITHM) {
case ONE_PLUS_ONE_EA:
logger.info("Chosen search algorithm: (1+1)EA");
return new OnePlusOneEA<>(factory);
case MU_PLUS_LAMBDA_EA:
logger.info("Chosen search algorithm: (Mu+Lambda)EA");
return new MuPlusLambdaEA<>(factory, Properties.MU, Properties.LAMBDA);
case MU_LAMBDA_EA:
logger.info("Chosen search algorithm: (Mu,Lambda)EA");
return new MuLambdaEA(factory, Properties.MU, Properties.LAMBDA);
case BREEDER_GA:
logger.info("Chosen search algorithm: BreederGA");
return new BreederGA<>(factory);
case MONOTONIC_GA:
logger.info("Chosen search algorithm: MonotonicGA");
{
MonotonicGA ga = new MonotonicGA<>(factory);
if (Properties.REPLACEMENT_FUNCTION == TheReplacementFunction.FITNESSREPLACEMENT) {
// user has explicitly asked for this replacement function
ga.setReplacementFunction(new FitnessReplacementFunction());
} else {
ga.setReplacementFunction(new TestCaseReplacementFunction());
}
return ga;
}
case CELLULAR_GA:
logger.info("Chosen search algorithm: CellularGA");
{
CellularGA ga = new CellularGA(Properties.MODEL, factory);
if (Properties.REPLACEMENT_FUNCTION == TheReplacementFunction.FITNESSREPLACEMENT) {
// user has explicitly asked for this replacement function
ga.setReplacementFunction(new FitnessReplacementFunction());
} else {
ga.setReplacementFunction(new TestCaseReplacementFunction());
}
return ga;
}
case STEADY_STATE_GA:
logger.info("Chosen search algorithm: Steady-StateGA");
{
SteadyStateGA ga = new SteadyStateGA<>(factory);
if (Properties.REPLACEMENT_FUNCTION == TheReplacementFunction.FITNESSREPLACEMENT) {
// user has explicitly asked for this replacement function
ga.setReplacementFunction(new FitnessReplacementFunction());
} else {
// use default
ga.setReplacementFunction(new TestCaseReplacementFunction());
}
return ga;
}
case RANDOM_SEARCH:
logger.info("Chosen search algorithm: Random");
return new RandomSearch<>(factory);
case NSGAII:
logger.info("Chosen search algorithm: NSGAII");
return new NSGAII<>(factory);
case SPEA2:
logger.info("Chosen search algorithm: SPEA2");
return new SPEA2<>(factory);
case ONE_PLUS_LAMBDA_LAMBDA_GA:
logger.info("Chosen search algorithm: 1 + (lambda, lambda)GA");
return new OnePlusLambdaLambdaGA<>(factory, Properties.LAMBDA);
case STANDARD_CHEMICAL_REACTION:
logger.info("Chosen search algorithm: Standard Chemical Reaction Optimization");
return new StandardChemicalReaction<>(factory);
case LIPS:
logger.info("Chosen search algorithm: LIPS");
return new LIPS(factory);
default:
logger.info("Chosen search algorithm: StandardGA");
return new StandardGA<>(factory);
}
}
private SelectionFunction getSelectionFunction() {
switch (Properties.SELECTION_FUNCTION) {
case ROULETTEWHEEL:
return new FitnessProportionateSelection<>();
case TOURNAMENT:
return new TournamentSelection<>();
case BINARY_TOURNAMENT:
return new BinaryTournamentSelectionCrowdedComparison<>();
case RANK_CROWD_DISTANCE_TOURNAMENT:
return new TournamentSelectionRankAndCrowdingDistanceComparator<>();
default:
return new RankSelection<>();
}
}
private CrossOverFunction getCrossoverFunction() {
switch (Properties.CROSSOVER_FUNCTION) {
case SINGLEPOINTFIXED:
return new SinglePointFixedCrossOver();
case SINGLEPOINTRELATIVE:
return new SinglePointRelativeCrossOver();
case SINGLEPOINT:
return new SinglePointCrossOver();
case UNIFORM:
return new UniformCrossOver();
default:
throw new RuntimeException("Unknown crossover function: "
+ Properties.CROSSOVER_FUNCTION);
}
}
private RankingFunction getRankingFunction() {
switch (Properties.RANKING_TYPE) {
case FAST_NON_DOMINATED_SORTING:
return new FastNonDominatedSorting<>();
case PREFERENCE_SORTING:
default:
return new RankBasedPreferenceSorting<>();
}
}
@Override
public GeneticAlgorithm getSearchAlgorithm() {
ChromosomeFactory factory = getChromosomeFactory();
// FIXXME
GeneticAlgorithm ga = getGeneticAlgorithm(factory);
if (Properties.NEW_STATISTICS)
ga.addListener(new org.evosuite.statistics.StatisticsListener());
// How to select candidates for reproduction
SelectionFunction selection_function = getSelectionFunction();
selection_function.setMaximize(false);
ga.setSelectionFunction(selection_function);
RankingFunction ranking_function = getRankingFunction();
ga.setRankingFunction(ranking_function);
// When to stop the search
StoppingCondition stopping_condition = getStoppingCondition();
ga.setStoppingCondition(stopping_condition);
// ga.addListener(stopping_condition);
if (Properties.STOP_ZERO) {
ga.addStoppingCondition(new ZeroFitnessStoppingCondition());
}
if (!(stopping_condition instanceof MaxTimeStoppingCondition)) {
ga.addStoppingCondition(new GlobalTimeStoppingCondition());
}
if (ArrayUtil.contains(Properties.CRITERION, Criterion.MUTATION)
|| ArrayUtil.contains(Properties.CRITERION, Criterion.STRONGMUTATION)) {
ga.addStoppingCondition(new MutationTimeoutStoppingCondition());
}
ga.resetStoppingConditions();
ga.setPopulationLimit(getPopulationLimit());
// How to cross over
CrossOverFunction crossover_function = getCrossoverFunction();
ga.setCrossOverFunction(crossover_function);
// What to do about bloat
// MaxLengthBloatControl bloat_control = new MaxLengthBloatControl();
// ga.setBloatControl(bloat_control);
if (Properties.CHECK_BEST_LENGTH) {
org.evosuite.testcase.RelativeTestLengthBloatControl bloat_control = new org.evosuite.testcase.RelativeTestLengthBloatControl();
ga.addBloatControl(bloat_control);
ga.addListener(bloat_control);
}
TestCaseSecondaryObjective.setSecondaryObjectives();
if (Properties.DYNAMIC_LIMIT) {
// max_s = GAProperties.generations * getBranches().size();
// TODO: might want to make this dependent on the selected coverage
// criterion
// TODO also, question: is branchMap.size() really intended here?
// I think BranchPool.getBranchCount() was intended
Properties.SEARCH_BUDGET = Properties.SEARCH_BUDGET
* (BranchPool.getInstance(TestGenerationContext.getInstance().getClassLoaderForSUT()).getNumBranchlessMethods(Properties.TARGET_CLASS) + BranchPool.getInstance(TestGenerationContext.getInstance().getClassLoaderForSUT()).getBranchCountForClass(Properties.TARGET_CLASS) * 2);
stopping_condition.setLimit(Properties.SEARCH_BUDGET);
logger.info("Setting dynamic length limit to " + Properties.SEARCH_BUDGET);
}
// TODO: This seems to be whole test suite specific
// if (Properties.LOCAL_SEARCH_RESTORE_COVERAGE) {
// ga.addListener(BranchCoverageMap.getInstance());
// }
if (Properties.RECYCLE_CHROMOSOMES) {
if (Properties.STRATEGY == Strategy.ONEBRANCH)
ga.addListener(TestCaseRecycler.getInstance());
}
// ga.addListener(new ResourceController());
return ga;
}
}