31619759710

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/algorithms/active/ttt/src/main/java/de/learnlib/algorithm/ttt/base/AbstractTTTLearner.java

/* Copyright (C) 2013-2026 TU Dortmund University
 * This file is part of LearnLib <https://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.base;

import java.util.ArrayDeque;
import java.util.ArrayList;
import java.util.Collection;
import java.util.Collections;
import java.util.Deque;
import java.util.HashMap;
import java.util.HashSet;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
import java.util.Objects;
import java.util.Set;

import de.learnlib.AccessSequenceTransformer;
import de.learnlib.LearnerStateTracker;
import de.learnlib.Resumable;
import de.learnlib.acex.AcexAnalyzer;
import de.learnlib.acex.AcexAnalyzers;
import de.learnlib.acex.OutInconsPrefixTransformAcex;
import de.learnlib.algorithm.LearningAlgorithm;
import de.learnlib.datastructure.discriminationtree.SplitData;
import de.learnlib.datastructure.list.IntrusiveList;
import de.learnlib.logging.Category;
import de.learnlib.oracle.MembershipOracle;
import de.learnlib.query.DefaultQuery;
import de.learnlib.query.Query;
import net.automatalib.alphabet.Alphabet;
import net.automatalib.alphabet.SupportsGrowingAlphabet;
import net.automatalib.common.smartcollection.ElementReference;
import net.automatalib.common.smartcollection.UnorderedCollection;
import net.automatalib.common.util.collection.CollectionUtil;
import net.automatalib.word.Word;
import org.checkerframework.checker.nullness.qual.Nullable;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

/**
 * The TTT learning algorithm for generic automata.
 * <p>
 * <b>Implementation note:</b> this learner uses the {@link AccessSequenceTransformer} interface to provide access to
 * the representatives of the states of the current hypothesis model.
 *
 * @param <A>
 *         hypothesis automaton type
 * @param <I>
 *         input symbol type
 * @param <D>
 *         output domain type
 */
public abstract class AbstractTTTLearner<A, I, D> implements LearningAlgorithm<A, I, D>,
                                                             AccessSequenceTransformer<I>,
                                                             SupportsGrowingAlphabet<I>,
                                                             Resumable<TTTLearnerState<I, D>>,
                                                             LearnerStateTracker {

    private static final Logger LOGGER = LoggerFactory.getLogger(AbstractTTTLearner.class);

    protected final Alphabet<I> alphabet;
    protected final MembershipOracle<I, D> oracle;
    protected final AcexAnalyzer analyzer;
    /**
     * Open transitions, i.e., transitions that possibly point to a non-leaf node in the discrimination tree.
     */
    protected final IntrusiveList<TTTTransition<I, D>> openTransitions = new IntrusiveList<>();
    /**
     * The blocks during a split operation. A block is a maximal subtree of the discrimination tree containing temporary
     * discriminators at its root.
     */
    protected final IntrusiveList<AbstractBaseDTNode<I, D>> blockList = new IntrusiveList<>();
    protected AbstractTTTHypothesis<?, I, D, ?> hypothesis;
    protected BaseTTTDiscriminationTree<I, D> dtree;

    protected AbstractTTTLearner(Alphabet<I> alphabet,
                                 MembershipOracle<I, D> oracle,
                                 AbstractTTTHypothesis<?, I, D, ?> hypothesis,
                                 BaseTTTDiscriminationTree<I, D> dtree,
                                 AcexAnalyzer analyzer) {
        this.alphabet = alphabet;
        this.hypothesis = hypothesis;
        this.oracle = oracle;
        this.dtree = dtree;
        this.analyzer = analyzer;
    }

    /**
     * Marks a node, and propagates the label up to all nodes on the path from the block root to this node.
     *
     * @param node
     *         the node to mark
     * @param label
     *         the label to mark the node with
     */
    private static <I, D> void markAndPropagate(AbstractBaseDTNode<I, D> node, D label) {
        AbstractBaseDTNode<I, D> curr = node;

        while (curr != null && curr.getSplitData() != null) {
            if (!curr.getSplitData().mark(label)) {
                return;
            }
            curr = curr.getParent();
        }
    }

    /**
     * Moves all transition from the "incoming" list (for a given label) of an old node to the "incoming" list of a new
     * node.
     *
     * @param newNode
     *         the new node
     * @param oldNode
     *         the old node
     * @param label
     *         the label to consider
     * @param <I>
     *         input symbol type
     * @param <D>
     *         output domain type
     */
    private static <I, D> void moveIncoming(AbstractBaseDTNode<I, D> newNode,
                                            AbstractBaseDTNode<I, D> oldNode,
                                            D label) {
        newNode.getIncoming().concat(oldNode.getSplitData().getIncoming(label));
    }

    /**
     * Establish the connection between a node in the discrimination tree and a state of the hypothesis.
     *
     * @param dtNode
     *         the node in the discrimination tree
     * @param state
     *         the state in the hypothesis
     * @param <I>
     *         input symbol type
     * @param <D>
     *         output domain type
     */
    protected static <I, D> void link(AbstractBaseDTNode<I, D> dtNode, TTTState<I, D> state) {
        assert dtNode.isLeaf();

        dtNode.setData(state);
        state.dtLeaf = dtNode;
    }

    /*
     * Private helper methods.
     */

    @Override
    public void startLearning() {
        requireLearningProcessNotStarted();

        TTTState<I, D> init = hypothesis.initialize();
        AbstractBaseDTNode<I, D> initNode = dtree.sift(init.getAccessSequence(), false);
        link(initNode, init);
        initializeState(init);

        closeTransitions();
    }

    @Override
    public boolean refineHypothesis(DefaultQuery<I, D> ceQuery) {
        requireLearningProcessStarted();

        if (!refineHypothesisSingle(ceQuery)) {
            return false;
        }

        while (refineHypothesisSingle(ceQuery)) {
            // refine exhaustively
        }

        return true;
    }

    @Override
    public boolean hasLearningProcessStarted() {
        return hypothesis.isInitialized();
    }

    /**
     * Initializes a state. Creates its outgoing transition objects, and adds them to the "open" list.
     *
     * @param state
     *         the state to initialize
     */
    protected void initializeState(TTTState<I, D> state) {
        TTTTransition<I, D> head = null;
        for (int i = 0; i < alphabet.size(); i++) {
            I sym = alphabet.getSymbol(i);
            TTTTransition<I, D> trans = createTransition(state, sym);
            trans.setNonTreeTarget(dtree.getRoot());
            state.setTransition(i, trans);
            openTransitions.add(trans);
            head = trans;
        }
        initTransitions(head, alphabet.size());
    }

    protected TTTTransition<I, D> createTransition(TTTState<I, D> state, I sym) {
        return new TTTTransition<>(state, sym);
    }

    /**
     * A post-processing hook for transitions created by {@link #createTransition(TTTState, Object)}, e.g., after
     * {@link #initializeState(TTTState)} or {@link #addAlphabetSymbol(Object)}. This is mainly useful for transition
     * output hypotheses that want to initialize the transition outputs in a bulk operation.
     *
     * @param head
     *         the head of (the list of) the created transitions
     * @param num
     *         the number of created transitions
     */
    protected void initTransitions(TTTTransition<I, D> head, int num) {}

    /**
     * Performs a single refinement of the hypothesis, i.e., without repeated counterexample evaluation. The parameter
     * and return value have the same significance as in {@link #refineHypothesis(DefaultQuery)}.
     *
     * @param ceQuery
     *         the counterexample (query) to be used for refinement
     *
     * @return {@code true} if the hypothesis was refined, {@code false} otherwise
     */
    protected boolean refineHypothesisSingle(DefaultQuery<I, D> ceQuery) {
        TTTState<I, D> state = getAnyState(ceQuery.getPrefix());
        D out = computeHypothesisOutput(state, ceQuery.getSuffix());

        if (Objects.equals(out, ceQuery.getOutput())) {
            return false;
        }

        OutputInconsistency<I, D> outIncons =
                new OutputInconsistency<>(state, ceQuery.getSuffix(), ceQuery.getOutput());

        do {
            splitState(outIncons);
            do {
                closeTransitions();
            } while (finalizeAny());

            outIncons = findOutputInconsistency();
        } while (outIncons != null);
        assert allNodesFinal();

        return true;
    }

    /**
     * Splits a state in the hypothesis, using a temporary discriminator. The state to be split is identified by an
     * incoming non-tree transition. This transition is subsequently turned into a spanning tree transition.
     *
     * @param transition
     *         the transition
     * @param tempDiscriminator
     *         the temporary discriminator
     */
    private void splitState(TTTTransition<I, D> transition, Word<I> tempDiscriminator, D oldOut, D newOut) {
        assert !transition.isTree();

        AbstractBaseDTNode<I, D> dtNode = transition.getNonTreeTarget();
        assert dtNode.isLeaf();
        TTTState<I, D> oldState = dtNode.getData();
        assert oldState != null;

        TTTState<I, D> newState = makeTree(transition);

        AbstractBaseDTNode<I, D>.SplitResult children = dtNode.split(tempDiscriminator, oldOut, newOut);
        dtNode.setTemp(true);

        link(children.nodeOld, oldState);
        link(children.nodeNew, newState);

        if (dtNode.getParent() == null || !dtNode.getParent().isTemp()) {
            blockList.add(dtNode);
        }
    }

    private void splitState(OutputInconsistency<I, D> outIncons) {

        OutInconsPrefixTransformAcex<I, D> acex = deriveAcex(outIncons);
        try {
            int breakpoint = analyzer.analyzeAbstractCounterexample(acex);
            assert !acex.testEffects(breakpoint, breakpoint + 1);

            Word<I> suffix = outIncons.suffix;

            TTTState<I, D> predState = getDeterministicState(outIncons.srcState, suffix.prefix(breakpoint));
            TTTState<I, D> succState = getDeterministicState(outIncons.srcState, suffix.prefix(breakpoint + 1));
            assert getDeterministicState(predState, Word.fromLetter(suffix.getSymbol(breakpoint))) == succState;

            I sym = suffix.getSymbol(breakpoint);
            Word<I> splitSuffix = suffix.subWord(breakpoint + 1);
            TTTTransition<I, D> trans = predState.getTransition(alphabet.getSymbolIndex(sym));
            assert !trans.isTree();
            D oldOut = acex.effect(breakpoint + 1);
            D newOut = succEffect(acex.effect(breakpoint));

            splitState(trans, splitSuffix, oldOut, newOut);
        } catch (HypothesisChangedException ignored) {
            // ignore
        }
    }

    protected OutInconsPrefixTransformAcex<I, D> deriveAcex(OutputInconsistency<I, D> outIncons) {
        TTTState<I, D> source = outIncons.srcState;
        Word<I> suffix = outIncons.suffix;

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

        acex.setEffect(0, outIncons.targetOut);
        return acex;
    }

    protected abstract D succEffect(D effect);

    /**
     * Chooses a block root, and finalizes the corresponding discriminator.
     *
     * @return {@code true} if a splittable block root was found, {@code false} otherwise.
     */
    protected boolean finalizeAny() {
        GlobalSplitter<I, D> splitter = findSplitterGlobal();
        if (splitter != null) {
            finalizeDiscriminator(splitter.blockRoot, splitter.localSplitter);
            return true;
        }
        return false;
    }

    protected TTTState<I, D> getDeterministicState(TTTState<I, D> start, Word<I> word) {
        TTTState<I, D> lastSingleton = start;
        int lastSingletonIndex = 0;

        Set<TTTState<I, D>> states = Collections.singleton(start);
        int i = 1;
        for (I sym : word) {
            Set<TTTState<I, D>> nextStates = getNonDetSuccessors(states, sym);
            if (nextStates.size() == 1) {
                lastSingleton = nextStates.iterator().next();
                lastSingletonIndex = i;
            }
            states = nextStates;

            i++;
        }
        if (lastSingletonIndex == word.length()) {
            return lastSingleton;
        }

        TTTState<I, D> curr = lastSingleton;
        for (I sym : word.subWord(lastSingletonIndex)) {
            TTTTransition<I, D> trans = curr.getTransition(alphabet.getSymbolIndex(sym));
            curr = requireSuccessor(trans);
        }

        return curr;
    }

    protected Set<TTTState<I, D>> getNonDetSuccessors(Collection<? extends TTTState<I, D>> states, I sym) {
        Set<TTTState<I, D>> result = new HashSet<>();
        int symIdx = alphabet.getSymbolIndex(sym);
        for (TTTState<I, D> state : states) {
            TTTTransition<I, D> trans = state.getTransition(symIdx);
            if (trans.isTree()) {
                result.add(trans.getTreeTarget());
            } else {
                AbstractBaseDTNode<I, D> tgtNode = trans.getNonTreeTarget();
                CollectionUtil.add(result, tgtNode.subtreeStatesIterator());
            }
        }
        return result;
    }

    protected TTTState<I, D> getAnySuccessor(TTTState<I, D> state, I sym) {
        int symIdx = alphabet.getSymbolIndex(sym);
        TTTTransition<I, D> trans = state.getTransition(symIdx);
        if (trans.isTree()) {
            return trans.getTreeTarget();
        }
        return trans.getNonTreeTarget().subtreeStatesIterator().next();
    }

    protected TTTState<I, D> getAnySuccessor(TTTState<I, D> state, Iterable<? extends I> suffix) {
        TTTState<I, D> curr = state;
        for (I sym : suffix) {
            curr = getAnySuccessor(curr, sym);
        }
        return curr;
    }

    private TTTState<I, D> requireSuccessor(TTTTransition<I, D> trans) {
        if (trans.isTree()) {
            return trans.getTreeTarget();
        }
        AbstractBaseDTNode<I, D> newTgtNode = updateDTTarget(trans, true);
        if (newTgtNode.getData() == null) {
            makeTree(trans);
            closeTransitions();
            // FIXME: using exception handling for this is not very nice, but it appears there
            // is no quicker way to abort counterexample analysis
            throw new HypothesisChangedException();
        }
        return newTgtNode.getData();
    }

    /**
     * Determines a global splitter, i.e., a splitter for any block. This method may (but is not required to) employ
     * heuristics to obtain a splitter with a relatively short suffix length.
     *
     * @return a splitter for any of the blocks
     */
    private @Nullable GlobalSplitter<I, D> findSplitterGlobal() {
        // TODO: Make global option
        boolean optimizeGlobal = true;

        AbstractBaseDTNode<I, D> bestBlockRoot = null;

        Splitter<I, D> bestSplitter = null;

        for (AbstractBaseDTNode<I, D> blockRoot : blockList) {
            Splitter<I, D> splitter = findSplitter(blockRoot);

            if (splitter != null) {
                if (bestSplitter == null || splitter.getDiscriminatorLength() < bestSplitter.getDiscriminatorLength()) {
                    bestSplitter = splitter;
                    bestBlockRoot = blockRoot;
                }

                if (!optimizeGlobal) {
                    break;
                }
            }
        }

        if (bestSplitter == null) {
            return null;
        }

        return new GlobalSplitter<>(bestBlockRoot, bestSplitter);
    }

    /**
     * Determines a (local) splitter for a given block. This method may (but is not required to) employ heuristics to
     * obtain a splitter with a relatively short suffix.
     *
     * @param blockRoot
     *         the root of the block
     *
     * @return a splitter for this block, or {@code null} if no such splitter could be found.
     */
    private @Nullable Splitter<I, D> findSplitter(AbstractBaseDTNode<I, D> blockRoot) {
        int alphabetSize = alphabet.size();

        @Nullable Object[] properties = new Object[alphabetSize];
        @SuppressWarnings("unchecked")
        AbstractBaseDTNode<I, D>[] lcas = new AbstractBaseDTNode[alphabetSize];
        boolean first = true;

        for (TTTState<I, D> state : blockRoot.subtreeStates()) {
            for (int i = 0; i < alphabetSize; i++) {
                TTTTransition<I, D> trans = state.getTransition(i);
                if (first) {
                    properties[i] = trans.getProperty();
                    lcas[i] = trans.getDTTarget();
                } else {
                    if (!Objects.equals(properties[i], trans.getProperty())) {
                        return new Splitter<>(i);
                    }
                    lcas[i] = dtree.leastCommonAncestor(lcas[i], trans.getDTTarget());
                }
            }
            first = false;
        }

        int shortestLen = Integer.MAX_VALUE;
        AbstractBaseDTNode<I, D> shortestLca = null;
        int shortestLcaSym = -1;

        for (int i = 0; i < alphabetSize; i++) {
            AbstractBaseDTNode<I, D> lca = lcas[i];
            if (!lca.isTemp() && !lca.isLeaf()) {
                int lcaLen = lca.getDiscriminator().length();
                if (shortestLca == null || lcaLen < shortestLen) {
                    shortestLca = lca;
                    shortestLen = lcaLen;
                    shortestLcaSym = i;
                }
            }
        }

        if (shortestLca != null) {
            return new Splitter<>(shortestLcaSym, shortestLca);
        }
        return null;
    }

    /**
     * Creates a state in the hypothesis. This method cannot be used for the initial state, which has no incoming tree
     * transition.
     *
     * @param transition
     *         the "parent" transition in the spanning tree
     *
     * @return the newly created state
     */
    private TTTState<I, D> createState(TTTTransition<I, D> transition) {
        return hypothesis.createState(transition);
    }

    /**
     * Retrieves the target state of a given transition. This method works for both tree and non-tree transitions. If a
     * non-tree transition points to a non-leaf node, it is updated accordingly before a result is obtained.
     *
     * @param trans
     *         the transition
     *
     * @return the target state of this transition (possibly after it having been updated)
     */
    protected TTTState<I, D> getAnyTarget(TTTTransition<I, D> trans) {
        if (trans.isTree()) {
            return trans.getTreeTarget();
        }
        return trans.getNonTreeTarget().anySubtreeState();
    }

    /**
     * Retrieves the state reached by the given sequence of symbols, starting from the initial state.
     *
     * @param suffix
     *         the sequence of symbols to process
     *
     * @return the state reached after processing the specified symbols
     */
    private TTTState<I, D> getAnyState(Iterable<? extends I> suffix) {
        return getAnySuccessor(hypothesis.getInitialState(), suffix);
    }

    protected OutputInconsistency<I, D> findOutputInconsistency() {
        OutputInconsistency<I, D> best = null;

        for (TTTState<I, D> state : hypothesis.getStates()) {
            AbstractBaseDTNode<I, D> node = state.getDTLeaf();
            while (!node.isRoot()) {
                D expectedOut = node.getParentOutcome();
                node = node.getParent();
                Word<I> suffix = node.getDiscriminator();
                if (best == null || suffix.length() < best.suffix.length()) {
                    D hypOut = computeHypothesisOutput(state, suffix);
                    if (!Objects.equals(hypOut, expectedOut)) {
                        best = new OutputInconsistency<>(state, suffix, expectedOut);
                    }
                }
            }
        }
        return best;
    }

    /**
     * Finalize a discriminator. Given a block root and a {@link Splitter}, replace the discriminator at the block root
     * by the one derived from the splitter, and update the discrimination tree accordingly.
     *
     * @param blockRoot
     *         the block root whose discriminator to finalize
     * @param splitter
     *         the splitter to use for finalization
     */
    private void finalizeDiscriminator(AbstractBaseDTNode<I, D> blockRoot, Splitter<I, D> splitter) {
        assert blockRoot.isBlockRoot();

        Word<I> succDiscr = splitter.getDiscriminator().prepend(alphabet.getSymbol(splitter.symbolIdx));

        if (!blockRoot.getDiscriminator().equals(succDiscr)) {
            Word<I> finalDiscriminator = prepareSplit(blockRoot, splitter);
            Map<D, AbstractBaseDTNode<I, D>> repChildren = createMap();
            for (D label : blockRoot.getSplitData().getLabels()) {
                repChildren.put(label, extractSubtree(blockRoot, label));
            }
            blockRoot.replaceChildren(repChildren);

            blockRoot.setDiscriminator(finalDiscriminator);
        }

        declareFinal(blockRoot);
    }

    protected boolean allNodesFinal() {
        Iterator<AbstractBaseDTNode<I, D>> it = dtree.getRoot().subtreeNodesIterator();
        while (it.hasNext()) {
            AbstractBaseDTNode<I, D> node = it.next();
            assert !node.isTemp() : "Final node with discriminator " + node.getDiscriminator();
        }
        return true;
    }

    protected void declareFinal(AbstractBaseDTNode<I, D> blockRoot) {
        blockRoot.setTemp(false);
        blockRoot.setSplitData(null);

        blockRoot.removeFromList();

        for (AbstractBaseDTNode<I, D> subtree : blockRoot.getChildren()) {
            assert subtree.getSplitData() == null;
            blockRoot.setChild(subtree.getParentOutcome(), subtree);
            // Register as blocks, if they are non-trivial subtrees
            if (subtree.isInner()) {
                blockList.add(subtree);
            }
        }
        openTransitions.concat(blockRoot.getIncoming());
    }

    /**
     * Prepare a split operation on a block, by marking all the nodes and transitions in the subtree (and annotating
     * them with {@link SplitData} objects).
     *
     * @param node
     *         the block root to be split
     * @param splitter
     *         the splitter to use for splitting the block
     *
     * @return the discriminator to use for splitting
     */
    private Word<I> prepareSplit(AbstractBaseDTNode<I, D> node, Splitter<I, D> splitter) {
        int symbolIdx = splitter.symbolIdx;
        I symbol = alphabet.getSymbol(symbolIdx);
        Word<I> discriminator = splitter.getDiscriminator().prepend(symbol);

        Deque<AbstractBaseDTNode<I, D>> dfsStack = new ArrayDeque<>();
        List<SplitQuery<I, D>> queries = new ArrayList<>();

        AbstractBaseDTNode<I, D> succSeparator = splitter.succSeparator;

        dfsStack.push(node);
        assert node.getSplitData() == null;

        while (!dfsStack.isEmpty()) {
            AbstractBaseDTNode<I, D> curr = dfsStack.pop();
            assert curr.getSplitData() == null;

            curr.setSplitData(new SplitData<>(IntrusiveList::new));

            for (TTTTransition<I, D> trans : curr.getIncoming()) {
                queries.add(new SplitQuery<>(trans, discriminator));
            }

            if (!queries.isEmpty()) {
                oracle.processQueries(queries);

                for (SplitQuery<I, D> query : queries) {
                    curr.getSplitData().getIncoming(query.output).add(query.transition);
                    markAndPropagate(curr, query.output);
                }

                queries.clear();
            }

            if (curr.isInner()) {
                for (AbstractBaseDTNode<I, D> child : curr.getChildren()) {
                    dfsStack.push(child);
                }
            } else {
                TTTState<I, D> state = curr.getData();
                assert state != null;

                TTTTransition<I, D> trans = state.getTransition(symbolIdx);
                D outcome = predictSuccOutcome(trans, succSeparator);
                assert outcome != null;
                curr.getSplitData().setStateLabel(outcome);
                markAndPropagate(curr, outcome);
            }

        }

        return discriminator;
    }

    protected abstract D predictSuccOutcome(TTTTransition<I, D> trans, AbstractBaseDTNode<I, D> succSeparator);

    /**
     * Extract a (reduced) subtree containing all nodes with the given label from the subtree given by its root.
     * "Reduced" here refers to the fact that the resulting subtree will contain no inner nodes with only one child.
     * <p>
     * The tree returned by this method (represented by its root) will have as a parent node the root that was passed to
     * this method.
     *
     * @param root
     *         the root of the subtree from which to extract
     * @param label
     *         the label of the nodes to extract
     *
     * @return the extracted subtree
     */
    private AbstractBaseDTNode<I, D> extractSubtree(AbstractBaseDTNode<I, D> root, D label) {
        assert root.getSplitData() != null;
        assert root.getSplitData().isMarked(label);

        Deque<ExtractRecord<I, D>> stack = new ArrayDeque<>();

        AbstractBaseDTNode<I, D> firstExtracted = createNewNode(root, label);

        stack.push(new ExtractRecord<>(root, firstExtracted));
        while (!stack.isEmpty()) {
            ExtractRecord<I, D> curr = stack.pop();

            AbstractBaseDTNode<I, D> original = curr.original;
            AbstractBaseDTNode<I, D> extracted = curr.extracted;

            moveIncoming(extracted, original, label);

            if (original.isLeaf()) {
                if (Objects.equals(original.getSplitData().getStateLabel(), label)) {
                    link(extracted, original.getData());
                } else {
                    createNewState(extracted);
                }
                extracted.updateIncoming();
            } else {
                List<AbstractBaseDTNode<I, D>> markedChildren = new ArrayList<>();

                for (AbstractBaseDTNode<I, D> child : original.getChildren()) {
                    if (child.getSplitData().isMarked(label)) {
                        markedChildren.add(child);
                    }
                }

                if (markedChildren.size() > 1) {
                    Map<D, AbstractBaseDTNode<I, D>> childMap = createMap();
                    for (AbstractBaseDTNode<I, D> c : markedChildren) {
                        D childLabel = c.getParentOutcome();
                        AbstractBaseDTNode<I, D> extractedChild = createNewNode(extracted, childLabel);
                        childMap.put(childLabel, extractedChild);
                        stack.push(new ExtractRecord<>(c, extractedChild));
                    }
                    extracted.setDiscriminator(original.getDiscriminator());
                    extracted.replaceChildren(childMap);
                    extracted.updateIncoming();
                    extracted.setTemp(true);
                } else if (markedChildren.size() == 1) {
                    stack.push(new ExtractRecord<>(markedChildren.get(0), extracted));
                } else { // markedChildren.isEmpty()
                    createNewState(extracted);
                    extracted.updateIncoming();
                }
            }

            assert extracted.getSplitData() == null;
        }

        return firstExtracted;
    }

    protected <V> Map<D, V> createMap() {
        return new HashMap<>();
    }

    /**
     * Create a new state during extraction on-the-fly. This is required if a node in the DT has an incoming transition
     * with a certain label, but in its subtree there are no leaves with this label as their state label.
     *
     * @param newNode
     *         the extracted node
     */
    private void createNewState(AbstractBaseDTNode<I, D> newNode) {
        TTTTransition<I, D> newTreeTrans = newNode.getIncoming().choose();
        assert newTreeTrans != null;

        TTTState<I, D> newState = createState(newTreeTrans);
        link(newNode, newState);
        initializeState(newState);
    }

    protected abstract D computeHypothesisOutput(TTTState<I, D> state, Word<I> suffix);

    public AbstractTTTHypothesis<?, I, D, ?> getHypothesisDS() {
        requireLearningProcessStarted();
        return hypothesis;
    }

    protected void closeTransitions() {
        UnorderedCollection<AbstractBaseDTNode<I, D>> newStateNodes = new UnorderedCollection<>();

        do {
            newStateNodes.addAll(closeTransitions(openTransitions, false));
            if (!newStateNodes.isEmpty()) {
                addNewStates(newStateNodes);
            }
        } while (!openTransitions.isEmpty());
    }

    /**
     * Ensures that the specified transitions point to a leaf-node. If a transition is a tree transition, this method
     * has no effect.
     * <p>
     * The provided transList is consumed in this process.
     * <p>
     * If a transition needs sifting, the reached leaf node will be collected in the returned collection.
     *
     * @param transList
     *         the list of transitions
     *
     * @return a collection containing the reached leaves of transitions that needed sifting
     */
    private List<AbstractBaseDTNode<I, D>> closeTransitions(IntrusiveList<TTTTransition<I, D>> transList,
                                                            boolean hard) {

        final List<TTTTransition<I, D>> transToSift = new ArrayList<>(transList.size());

        TTTTransition<I, D> t;
        while ((t = transList.poll()) != null) {
            if (!t.isTree()) {
                transToSift.add(t);
            }
        }

        if (transToSift.isEmpty()) {
            return Collections.emptyList();
        }

        final Iterator<AbstractBaseDTNode<I, D>> leavesIter = updateDTTargets(transToSift, hard).iterator();
        final List<AbstractBaseDTNode<I, D>> result = new ArrayList<>(transToSift.size());

        for (TTTTransition<I, D> transition : transToSift) {
            final AbstractBaseDTNode<I, D> node = leavesIter.next();
            if (node.isLeaf() && node.getData() == null && transition.getNext() == null) {
                result.add(node);
            }
        }

        assert !leavesIter.hasNext();
        return result;
    }

    private void addNewStates(UnorderedCollection<AbstractBaseDTNode<I, D>> newStateNodes) {
        AbstractBaseDTNode<I, D> minTransNode = null;
        TTTTransition<I, D> minTrans = null;
        int minAsLen = Integer.MAX_VALUE;
        ElementReference minTransNodeRef = null;
        for (ElementReference ref : newStateNodes.references()) {
            AbstractBaseDTNode<I, D> newStateNode = newStateNodes.get(ref);
            for (TTTTransition<I, D> trans : newStateNode.getIncoming()) {
                Word<I> as = trans.getAccessSequence();
                int asLen = as.length();
                if (asLen < minAsLen) {
                    minTransNode = newStateNode;
                    minTrans = trans;
                    minAsLen = asLen;
                    minTransNodeRef = ref;
                }
            }
        }

        assert minTransNode != null;
        newStateNodes.remove(minTransNodeRef);
        TTTState<I, D> state = makeTree(minTrans);
        link(minTransNode, state);
        initializeState(state);
    }

    protected TTTState<I, D> makeTree(TTTTransition<I, D> trans) {
        assert !trans.isTree();
        AbstractBaseDTNode<I, D> node = trans.nonTreeTarget;
        assert node.isLeaf();
        TTTState<I, D> state = createState(trans);
        trans.removeFromList();
        link(node, state);
        initializeState(state);
        return state;
    }

    /**
     * Updates the transition to point to either a leaf in the discrimination tree, or---if the {@code hard} parameter
     * is set to {@code false}---to a block root.
     *
     * @param transition
     *         the transition
     * @param hard
     *         whether to consider leaves as sufficient targets only
     *
     * @return the new target node of the transition
     */
    private AbstractBaseDTNode<I, D> updateDTTarget(TTTTransition<I, D> transition, boolean hard) {
        if (transition.isTree()) {
            return transition.getTreeTarget().dtLeaf;
        }

        AbstractBaseDTNode<I, D> dt = transition.getNonTreeTarget();
        dt = dtree.sift(dt, transition.getAccessSequence(), hard);
        transition.setNonTreeTarget(dt);

        return dt;
    }

    /**
     * Bulk version of {@link #updateDTTarget(TTTTransition, boolean)}.
     */
    private List<AbstractBaseDTNode<I, D>> updateDTTargets(List<TTTTransition<I, D>> transitions, boolean hard) {

        final List<AbstractBaseDTNode<I, D>> nodes = new ArrayList<>(transitions.size());
        final List<Word<I>> prefixes = new ArrayList<>(transitions.size());

        for (TTTTransition<I, D> t : transitions) {
            if (!t.isTree()) {
                AbstractBaseDTNode<I, D> dt = t.getNonTreeTarget();

                nodes.add(dt);
                prefixes.add(t.getAccessSequence());
            }
        }

        final Iterator<AbstractBaseDTNode<I, D>> leavesIter = dtree.sift(nodes, prefixes, hard).iterator();
        final List<AbstractBaseDTNode<I, D>> result = new ArrayList<>(transitions.size());

        for (TTTTransition<I, D> t : transitions) {
            if (t.isTree()) {
                result.add(t.getTreeTarget().dtLeaf);
            } else {
                AbstractBaseDTNode<I, D> leaf = leavesIter.next();
                t.setNonTreeTarget(leaf);
                result.add(leaf);
            }
        }

        assert !leavesIter.hasNext();
        return result;
    }

    /**
     * Returns the discrimination tree.
     *
     * @return the discrimination tree
     */
    public BaseTTTDiscriminationTree<I, D> getDiscriminationTree() {
        return dtree;
    }

    @Override
    public Word<I> transformAccessSequence(Word<I> word) {
        requireLearningProcessStarted();
        final TTTState<I, D> s = hypothesis.getState(word);
        // we should only query defined paths
        assert s != null;
        return s.getAccessSequence();
    }

    @Override
    public void addAlphabetSymbol(I symbol) {

        if (!this.alphabet.containsSymbol(symbol)) {
            this.alphabet.asGrowingAlphabetOrThrowException().addSymbol(symbol);
        }

        this.hypothesis.addAlphabetSymbol(symbol);

        // check if we already have information about the symbol (then the transition is defined) so we don't post
        // redundant queries
        if (this.hypothesis.getInitialState() != null && this.hypothesis.getState(Word.fromLetter(symbol)) == null) {

            final int newSymbolIdx = this.alphabet.getSymbolIndex(symbol);
            TTTTransition<I, D> head = null;

            for (TTTState<I, D> s : this.hypothesis.getStates()) {
                final TTTTransition<I, D> trans = createTransition(s, symbol);
                trans.setNonTreeTarget(dtree.getRoot());
                s.setTransition(newSymbolIdx, trans);
                openTransitions.add(trans);
                head = trans;
            }

            this.initTransitions(head, this.hypothesis.size());
            this.closeTransitions();
        }
    }

    protected abstract AbstractBaseDTNode<I, D> createNewNode(AbstractBaseDTNode<I, D> parent, D parentOutput);

    @Override
    public TTTLearnerState<I, D> suspend() {
        return new TTTLearnerState<>(hypothesis, dtree);
    }

    @Override
    public void resume(TTTLearnerState<I, D> state) {
        this.hypothesis = state.getHypothesis();
        this.dtree = state.getDiscriminationTree();
        this.dtree.setOracle(oracle);

        final Alphabet<I> oldAlphabet = this.hypothesis.getInputAlphabet();
        if (!oldAlphabet.equals(this.alphabet)) {
            LOGGER.warn(Category.DATASTRUCTURE,
                        "The current alphabet '{}' differs from the resumed alphabet '{}'. Future behavior may be inconsistent",
                        this.alphabet,
                        oldAlphabet);
        }
    }

    public static final class BuilderDefaults {

        private BuilderDefaults() {
            // prevent instantiation
        }

        public static AcexAnalyzer analyzer() {
            return AcexAnalyzers.BINARY_SEARCH_BWD;
        }
    }

    /**
     * Data structure for representing a splitter.
     * <p>
     * A splitter is represented by an input symbol, and a DT node that separates the successors (wrt. the input symbol)
     * of the original states. From this, a discriminator can be obtained by prepending the input symbol to the
     * discriminator that labels the separating successor.
     * <p>
     * <b>Note:</b> as the discriminator finalization is applied to the root of a block and affects all nodes, there is
     * no need to store references to the source states from which this splitter was obtained.
     *
     * @param <I>
     *         input symbol type
     */
    public static final class Splitter<I, D> {

        public final int symbolIdx;
        public final AbstractBaseDTNode<I, D> succSeparator;

        public Splitter(int symbolIdx) {
            this.symbolIdx = symbolIdx;
            this.succSeparator = null;
        }

        public Splitter(int symbolIdx, AbstractBaseDTNode<I, D> succSeparator) {
            assert !succSeparator.isTemp() && succSeparator.isInner();

            this.symbolIdx = symbolIdx;
            this.succSeparator = succSeparator;
        }

        public Word<I> getDiscriminator() {
            return (succSeparator != null) ? succSeparator.getDiscriminator() : Word.epsilon();
        }

        public int getDiscriminatorLength() {
            return (succSeparator != null) ? succSeparator.getDiscriminator().length() : 0;
        }
    }

    /**
     * A global splitter. In addition to the information stored in a (local) {@link Splitter}, this class also stores
     * the block the local splitter applies to.
     *
     * @param <I>
     *         input symbol type
     */
    private static final class GlobalSplitter<I, D> {

        private final Splitter<I, D> localSplitter;
        private final AbstractBaseDTNode<I, D> blockRoot;

        GlobalSplitter(AbstractBaseDTNode<I, D> blockRoot, Splitter<I, D> localSplitter) {
            this.blockRoot = blockRoot;
            this.localSplitter = localSplitter;
        }
    }

    /**
     * Data structure required during an extract operation. The latter basically works by copying nodes that are
     * required in the extracted subtree, and this data structure is required to associate original nodes with their
     * extracted copies.
     *
     * @param <I>
     *         input symbol type
     */
    private static final class ExtractRecord<I, D> {

        private final AbstractBaseDTNode<I, D> original;
        private final AbstractBaseDTNode<I, D> extracted;

        ExtractRecord(AbstractBaseDTNode<I, D> original, AbstractBaseDTNode<I, D> extracted) {
            this.original = original;
            this.extracted = extracted;
        }
    }

    private static final class SplitQuery<I, D> extends Query<I, D> {

        private final TTTTransition<I, D> transition;
        private final Word<I> discriminator;
        private D output;

        SplitQuery(TTTTransition<I, D> transition, Word<I> discriminator) {
            this.transition = transition;
            this.discriminator = discriminator;
        }

        @Override
        public void answer(D output) {
            this.output = output;
        }

        @Override
        public Word<I> getPrefix() {
            return transition.getAccessSequence();
        }

        @Override
        public Word<I> getSuffix() {
            return discriminator;
        }
    }
}

LearnLib / learnlib / 31619759710

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