de.learnlib.algorithm.ttt.moore.TTTLearnerMoore Maven / Gradle / Ivy

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This artifact provides the implementation of the TTT algorithm as described in the paper "The TTT Algorithm: A Redundancy-Free Approach to Active Automata Learning" (https://doi.org/10.1007/978-3-319-11164-3_26) by Malte Isberner, Falk Howar, and Bernhard Steffen.
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/* Copyright (C) 2013-2023 TU Dortmund
 * This file is part of LearnLib, http://www.learnlib.de/.
 *
 * 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 de.learnlib.algorithm.ttt.moore;

import com.github.misberner.buildergen.annotations.GenerateBuilder;
import de.learnlib.acex.AcexAnalyzer;
import de.learnlib.acex.MooreOutInconsPrefixTransformAcex;
import de.learnlib.acex.OutInconsPrefixTransformAcex;
import de.learnlib.algorithm.LearningAlgorithm.MooreLearner;
import de.learnlib.algorithm.ttt.base.AbstractBaseDTNode;
import de.learnlib.algorithm.ttt.base.AbstractTTTLearner;
import de.learnlib.algorithm.ttt.base.BaseTTTDiscriminationTree;
import de.learnlib.algorithm.ttt.base.OutputInconsistency;
import de.learnlib.algorithm.ttt.base.TTTState;
import de.learnlib.algorithm.ttt.base.TTTTransition;
import de.learnlib.oracle.MembershipOracle;
import de.learnlib.query.DefaultQuery;
import de.learnlib.util.moore.MooreUtil;
import net.automatalib.alphabet.Alphabet;
import net.automatalib.automaton.transducer.MooreMachine;
import net.automatalib.word.Word;
import net.automatalib.word.WordBuilder;

/**
 * A {@link MooreMachine}-based specialization of the TTT learner.
 *
 * @param 
 *         input symbol type
 * @param 
 *         output symbols type
 */
public class TTTLearnerMoore extends AbstractTTTLearner, I, Word>
        implements MooreLearner {

    @GenerateBuilder(defaults = AbstractTTTLearner.BuilderDefaults.class)
    public TTTLearnerMoore(Alphabet alphabet, MembershipOracle> oracle, AcexAnalyzer analyzer) {
        super(alphabet,
              oracle,
              new TTTHypothesisMoore<>(alphabet),
              new BaseTTTDiscriminationTree<>(oracle, TTTDTNodeMoore::new),
              analyzer);

        dtree.getRoot().split(Word.epsilon(), oracle.answerQuery(Word.epsilon()));
    }

    @Override
    protected Word succEffect(Word effect) {
        return effect.subWord(1);
    }

    @Override
    protected Word predictSuccOutcome(TTTTransition> trans,
                                         AbstractBaseDTNode> succSeparator) {
        TTTStateMoore curr = (TTTStateMoore) trans.getSource();
        final Word label = succSeparator.subtreeLabel(trans.getDTTarget());
        assert label != null;
        return label.prepend(curr.getOutput());
    }

    @Override
    protected void initializeState(TTTState> state) {
        super.initializeState(state);

        TTTStateMoore mooreState = (TTTStateMoore) state;
        final Word label = dtree.getRoot().subtreeLabel(mooreState.getDTLeaf());
        assert label != null && !label.isEmpty();
        mooreState.setOutput(label.firstSymbol());
    }

    @Override
    @SuppressWarnings("unchecked")
    protected boolean refineHypothesisSingle(DefaultQuery> ceQuery) {
        DefaultQuery> shortenedCeQuery =
                MooreUtil.shortenCounterExample((TTTHypothesisMoore) hypothesis, ceQuery);
        return shortenedCeQuery != null && super.refineHypothesisSingle(shortenedCeQuery);
    }

    @Override
    protected OutInconsPrefixTransformAcex> deriveAcex(OutputInconsistency> outIncons) {
        TTTState> source = outIncons.srcState;
        Word suffix = outIncons.suffix;

        OutInconsPrefixTransformAcex> acex = new MooreOutInconsPrefixTransformAcex<>(suffix,
                                                                                                oracle,
                                                                                                w -> getDeterministicState(
                                                                                                        source,
                                                                                                        w).getAccessSequence());

        acex.setEffect(0, outIncons.targetOut);
        Word lastHypOut = computeHypothesisOutput(getAnySuccessor(source, suffix), Word.epsilon());
        acex.setEffect(suffix.length(), lastHypOut);

        return acex;
    }

    @Override
    protected Word computeHypothesisOutput(TTTState> state, Word suffix) {

        TTTStateMoore curr = (TTTStateMoore) state;

        WordBuilder wb = new WordBuilder<>(suffix.length());

        wb.append(curr.output);
        if (suffix.isEmpty()) {
            return wb.toWord();
        }

        for (I sym : suffix) {
            curr = (TTTStateMoore) getAnySuccessor(curr, sym);
            wb.append(curr.output);

        }
        return wb.toWord();

    }

    @Override
    protected AbstractBaseDTNode> createNewNode(AbstractBaseDTNode> parent,
                                                           Word parentOutput) {
        return new TTTDTNodeMoore<>(parent, parentOutput);
    }

    @Override
    @SuppressWarnings("unchecked") // parent class uses the same instance that we pass in the constructor
    public TTTHypothesisMoore getHypothesisModel() {
        return (TTTHypothesisMoore) hypothesis;
    }

}