cc.kave.commons.pointsto.evaluation.DefaultModule.java Source code

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Here is the source code for cc.kave.commons.pointsto.evaluation.DefaultModule.java

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/**
 * Copyright 2016 Simon Reu
 *
 * Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
 * the License. You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
 * an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
 * specific language governing permissions and limitations under the License.
 */
package cc.kave.commons.pointsto.evaluation;

import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.function.Predicate;

import org.apache.commons.math3.random.RandomGenerator;
import org.apache.commons.math3.random.Well19937c;
import org.eclipse.recommenders.commons.bayesnet.BayesianNetwork;

import com.google.inject.AbstractModule;
import com.google.inject.Provides;
import com.google.inject.Singleton;
import com.google.inject.TypeLiteral;

import cc.kave.commons.pointsto.evaluation.annotations.NumberOfCVFolds;
import cc.kave.commons.pointsto.evaluation.annotations.UsageFilter;
import cc.kave.commons.pointsto.evaluation.cv.CrossValidationFoldBuilder;
import cc.kave.commons.pointsto.evaluation.cv.ProjectCVFoldBuilder;
import cc.kave.commons.pointsto.evaluation.measures.AbstractMeasure;
import cc.kave.commons.pointsto.evaluation.measures.F1Measure;
import cc.kave.commons.pointsto.evaluation.measures.RRMeasure;
import cc.recommenders.evaluation.queries.QueryBuilder;
import cc.recommenders.mining.calls.MiningOptions;
import cc.recommenders.mining.calls.MiningOptions.Algorithm;
import cc.recommenders.mining.calls.MiningOptions.DistanceMeasure;
import cc.recommenders.mining.calls.ModelBuilder;
import cc.recommenders.mining.calls.QueryOptions;
import cc.recommenders.mining.calls.QueryOptions.QueryType;
import cc.recommenders.mining.calls.clustering.FeatureWeighter;
import cc.recommenders.mining.calls.pbn.PBNModelBuilder;
import cc.recommenders.mining.features.FeatureExtractor;
import cc.recommenders.mining.features.UsageFeatureExtractor;
import cc.recommenders.mining.features.UsageFeatureWeighter;
import cc.recommenders.usages.Query;
import cc.recommenders.usages.Usage;
import cc.recommenders.usages.features.UsageFeature;

public class DefaultModule extends AbstractModule {

    @Override
    protected void configure() {
        configCrossValidation();
        configOptions();

        configMeasure();

        bind(new TypeLiteral<Predicate<Usage>>() {
        }).annotatedWith(UsageFilter.class).to(PointsToUsageFilter.class);
        bind(ResultExporter.class).to(CSVExporter.class);

        // Executor for CVEvaluator
        int numThreads;
        if (System.getProperties().containsKey("evaluation.numthreads")) {
            numThreads = Integer.parseInt(System.getProperty("evaluation.numthreads"));
        } else {
            numThreads = Math.min(6, Runtime.getRuntime().availableProcessors());
        }
        ExecutorService executorService = Executors.newFixedThreadPool(numThreads);
        // ExecutorService executorService = Executors.newSingleThreadExecutor();
        bind(ExecutorService.class).toInstance(executorService);
    }

    private void configCrossValidation() {
        bind(int.class).annotatedWith(NumberOfCVFolds.class).toInstance(10);
        bind(CrossValidationFoldBuilder.class).to(ProjectCVFoldBuilder.class);
    }

    private void configOptions() {
        QueryOptions qOpts = new QueryOptions();
        qOpts.queryType = QueryType.NM;
        qOpts.minProbability = 0.3;
        qOpts.useClassContext = false;
        qOpts.useMethodContext = true;
        qOpts.useDefinition = true;
        qOpts.useParameterSites = false;
        qOpts.isIgnoringAfterFullRecall = false;
        bind(QueryOptions.class).toInstance(qOpts);

        MiningOptions mOpts = new MiningOptions();
        mOpts.setDistanceMeasure(DistanceMeasure.COSINE);
        mOpts.setAlgorithm(Algorithm.CANOPY);
        mOpts.setT1(0.151);
        mOpts.setT2(0.15);

        // mOpts.setFeatureDropping(false);
        mOpts.setFeatureDropping(true);
        bind(MiningOptions.class).toInstance(mOpts);
    }

    protected void configMeasure() {
        bind(AbstractMeasure.class).toInstance(new RRMeasure());
        // bind(AbstractMeasure.class).toInstance(new F1Measure());
    }

    @Provides
    public RandomGenerator provideRandomGenerator() {
        return new Well19937c(1457288501271L);
    }

    @Provides
    public FeatureWeighter<UsageFeature> provideFeatureWeighter(MiningOptions options) {
        return new UsageFeatureWeighter(options);
    }

    @Provides
    public FeatureExtractor<Usage, UsageFeature> provideFeatureExtractor(MiningOptions options) {
        return new UsageFeatureExtractor(options);
    }

    @Provides
    public ModelBuilder<UsageFeature, BayesianNetwork> provideModelBuilder() {
        return new PBNModelBuilder();
    }

    @Provides
    @Singleton
    public QueryBuilder<Usage, Query> provideQueryBuilder(RandomGenerator rndGenerator) {
        return new OneMissingQueryBuilder(rndGenerator);
    }

}