6433387082

Committed 06 Oct 2023 03:10PM UTC coverage: 92.296% (-0.007%) from 92.303%

Build # 6433387082

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mtf90

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update Falk's developer id

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/algorithms/active/ttt/src/main/java/de/learnlib/algorithms/ttt/moore/TTTHypothesisMoore.java

/* 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.algorithms.ttt.moore;

import de.learnlib.algorithms.ttt.base.AbstractTTTHypothesis;
import de.learnlib.algorithms.ttt.base.TTTTransition;
import net.automatalib.automata.UniversalDeterministicAutomaton;
import net.automatalib.automata.UniversalDeterministicAutomaton.FullIntAbstraction;
import net.automatalib.automata.transducers.MooreMachine;
import net.automatalib.words.Alphabet;
import net.automatalib.words.Word;

/**
 * A {@link MooreMachine}-based specialization of the TTT hypothesis.
 *
 * @param <I>
 *         input symbol type
 * @param <O>
 *         output symbol type
 */
public class TTTHypothesisMoore<I, O>
        extends AbstractTTTHypothesis<TTTStateMoore<I, O>, I, Word<O>, TTTStateMoore<I, O>>
        implements MooreMachine<TTTStateMoore<I, O>, I, TTTStateMoore<I, O>, O>,
                   FullIntAbstraction<TTTStateMoore<I, O>, O, Void> {

    /**
     * Constructor.
     *
     * @param alphabet
     *         the input alphabet
     */
    public TTTHypothesisMoore(Alphabet<I> alphabet) {
        super(alphabet);
    }

    @Override
    protected TTTStateMoore<I, O> mapTransition(TTTTransition<I, Word<O>> internalTransition) {
        return (TTTStateMoore<I, O>) internalTransition.getTarget();
    }

    @Override
    public O getStateProperty(int state) {
        TTTStateMoore<I, O> mooreState = states.get(state);
        return mooreState.getOutput();

    }

    @Override
    protected TTTStateMoore<I, O> newState(int alphabetSize, TTTTransition<I, Word<O>> parent, int id) {
        return new TTTStateMoore<>(alphabetSize, parent, id);
    }

    @Override
    public UniversalDeterministicAutomaton.FullIntAbstraction<TTTStateMoore<I, O>, O, Void> fullIntAbstraction(Alphabet<I> alphabet) {
        if (alphabet.equals(getInputAlphabet())) {
            return this;
        }
        return MooreMachine.super.fullIntAbstraction(alphabet);
    }

    @Override
    public O getStateOutput(TTTStateMoore<I, O> state) {
        return state.getOutput();
    }

    @Override
    public TTTStateMoore<I, O> getSuccessor(TTTStateMoore<I, O> transition) {
        return transition;
    }

    @Override
    public Void getTransitionProperty(TTTStateMoore<I, O> state) {
        return null;
    }
}

1	/* Copyright (C) 2013-2023 TU Dortmund
2	* This file is part of LearnLib, http://www.learnlib.de/.
3	*
4	* Licensed under the Apache License, Version 2.0 (the "License");
5	* you may not use this file except in compliance with the License.
6	* You may obtain a copy of the License at
7	*
8	* http://www.apache.org/licenses/LICENSE-2.0
9	*
10	* Unless required by applicable law or agreed to in writing, software
11	* distributed under the License is distributed on an "AS IS" BASIS,
12	* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13	* See the License for the specific language governing permissions and
14	* limitations under the License.
15	*/
16	package de.learnlib.algorithms.ttt.moore;
17
18	import de.learnlib.algorithms.ttt.base.AbstractTTTHypothesis;
19	import de.learnlib.algorithms.ttt.base.TTTTransition;
20	import net.automatalib.automata.UniversalDeterministicAutomaton;
21	import net.automatalib.automata.UniversalDeterministicAutomaton.FullIntAbstraction;
22	import net.automatalib.automata.transducers.MooreMachine;
23	import net.automatalib.words.Alphabet;
24	import net.automatalib.words.Word;
25
26	/**
27	* A {@link MooreMachine}-based specialization of the TTT hypothesis.
28	*
29	* @param <I>
30	* input symbol type
31	* @param <O>
32	* output symbol type
33	*/
34	public class TTTHypothesisMoore<I, O>
35	extends AbstractTTTHypothesis<TTTStateMoore<I, O>, I, Word<O>, TTTStateMoore<I, O>>
36	implements MooreMachine<TTTStateMoore<I, O>, I, TTTStateMoore<I, O>, O>,
37	FullIntAbstraction<TTTStateMoore<I, O>, O, Void> {
38
39	/**
40	* Constructor.
41	*
42	* @param alphabet
43	* the input alphabet
44	*/
45	public TTTHypothesisMoore(Alphabet<I> alphabet) {
46	super(alphabet);	2✔
47	}	2✔
48
49	@Override
50	protected TTTStateMoore<I, O> mapTransition(TTTTransition<I, Word<O>> internalTransition) {
51	return (TTTStateMoore<I, O>) internalTransition.getTarget();	2✔
52	}
53
54	@Override
55	public O getStateProperty(int state) {
56	TTTStateMoore<I, O> mooreState = states.get(state);	2✔
57	return mooreState.getOutput();	2✔
58
59	}
60
61	@Override
62	protected TTTStateMoore<I, O> newState(int alphabetSize, TTTTransition<I, Word<O>> parent, int id) {
63	return new TTTStateMoore<>(alphabetSize, parent, id);	2✔
64	}
65
66	@Override
67	public UniversalDeterministicAutomaton.FullIntAbstraction<TTTStateMoore<I, O>, O, Void> fullIntAbstraction(Alphabet<I> alphabet) {
68	if (alphabet.equals(getInputAlphabet())) {	2✔
69	return this;	2✔
70	}
71	return MooreMachine.super.fullIntAbstraction(alphabet);	×
72	}
73
74	@Override
75	public O getStateOutput(TTTStateMoore<I, O> state) {
76	return state.getOutput();	2✔
77	}
78
79	@Override
80	public TTTStateMoore<I, O> getSuccessor(TTTStateMoore<I, O> transition) {
81	return transition;	2✔
82	}
83
84	@Override
85	public Void getTransitionProperty(TTTStateMoore<I, O> state) {
86	return null;	2✔
87	}
88	}

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