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This artifact provides the implementation of the VPA adaption of the Observation-Pack learning algorithm as discussed in the PhD thesis "Foundations of Active Automata Learning: An Algorithmic Perspective" (https://dx.doi.org/10.17877/DE290R-16359) by Malte Isberner.

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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.observationpack.vpa.hypothesis;

/**
 * @param 
 *         input symbol type
 */
public class HypIntTrans extends AbstractHypTrans {

    public HypIntTrans(HypLoc src, I intSym) {
        super(src.getAccessSequence().append(intSym));
    }

}