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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.base;

/**
 * Class that contains all data that represent the internal state of the {@link AbstractTTTLearner} learner and its DFA
 * and Mealy implementations.
 *
 * @param 
 *         The input alphabet type.
 * @param 
 *         The output domain type.
 */
public class TTTLearnerState {

    private final AbstractTTTHypothesis hypothesis;
    private final BaseTTTDiscriminationTree discriminationTree;

    TTTLearnerState(AbstractTTTHypothesis hypothesis,
                    BaseTTTDiscriminationTree discriminationTree) {

        this.hypothesis = hypothesis;
        this.discriminationTree = discriminationTree;
    }

    AbstractTTTHypothesis getHypothesis() {
        return hypothesis;
    }

    BaseTTTDiscriminationTree getDiscriminationTree() {
        return discriminationTree;
    }
}