6673301747

Committed 27 Oct 2023 11:46PM UTC coverage: 91.986% (-1.3%) from 93.327%

Build # 6673301747

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push

github

Committed by

mtf90

Commit Message

merge the release and sign-artifacts profiles

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69.23

/api/src/main/java/de/learnlib/api/algorithm/PassiveLearningAlgorithm.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.api.algorithm;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collection;
import java.util.Collections;
import java.util.List;

import de.learnlib.api.query.DefaultQuery;
import net.automatalib.automaton.fsa.DFA;
import net.automatalib.automaton.fsa.FiniteStateAcceptor;
import net.automatalib.automaton.fsa.NFA;
import net.automatalib.automaton.transducer.MealyMachine;
import net.automatalib.automaton.transducer.MooreMachine;
import net.automatalib.word.Word;

public interface PassiveLearningAlgorithm<M, I, D> {

    void addSamples(Collection<? extends DefaultQuery<I, D>> samples);

    @SuppressWarnings("unchecked")
    default void addSamples(DefaultQuery<I, D>... samples) {
        addSamples(Arrays.asList(samples));
    }

    @SuppressWarnings("unchecked")
    default void addSamples(D output, Word<I>... words) {
        addSamples(output, Arrays.asList(words));
    }

    default void addSamples(D output, Collection<? extends Word<I>> words) {
        List<DefaultQuery<I, D>> queries = new ArrayList<>(words.size());
        for (Word<I> word : words) {
            queries.add(new DefaultQuery<>(word, output));
        }

        addSamples(queries);
    }

    default void addSample(Word<I> input, D output) {
        addSample(new DefaultQuery<>(input, output));
    }

    default void addSample(DefaultQuery<I, D> sample) {
        addSamples(Collections.singleton(sample));
    }

    /**
     * Computes the model given the previously added samples.
     * <p>
     * <b>Implementation note:</b> It is up to the implementation if this operation is repeatable or not, An
     * implementation may throw an {@link IllegalStateException} if additional samples are added after the first model
     * construction.
     *
     * @return the computed model
     */
    M computeModel();

    /**
     * Basic interface for passive learning algorithms that infer {@link DFA}s.
     *
     * @param <I>
     *         input symbol type
     */
    interface PassiveDFALearner<I> extends PassiveAcceptorLearner<DFA<?, I>, I> {}

    /**
     * Basic interface for passive learning algorithms that infer {@link MealyMachine Mealy machines}.
     *
     * @param <I>
     *         input symbol type
     * @param <O>
     *         output symbol type
     */
    interface PassiveMealyLearner<I, O> extends PassiveLearningAlgorithm<MealyMachine<?, I, ?, O>, I, Word<O>> {}

    /**
     * Basic interface for passive learning algorithms that infer {@link MooreMachine Moore machines}.
     *
     * @param <I>
     *         input symbol type
     * @param <O>
     *         output symbol type
     */
    interface PassiveMooreLearner<I, O> extends PassiveLearningAlgorithm<MooreMachine<?, I, ?, O>, I, Word<O>> {}

    /**
     * Basic interface for passive learning algorithms that infer finite-state acceptors ({@link DFA}s or {@link
     * NFA}s).
     *
     * @param <M>
     *         model type
     * @param <I>
     *         input symbol type
     */
    interface PassiveAcceptorLearner<M extends FiniteStateAcceptor<?, I>, I>
            extends PassiveLearningAlgorithm<M, I, Boolean> {

        default void addPositiveSample(Word<I> word) {
            addSample(word, true);
        }

        default void addPositiveSamples(Collection<? extends Word<I>> words) {
            addSamples(true, words);
        }

        @SuppressWarnings("unchecked")
        default void addPositiveSamples(Word<I>... words) {
            addSamples(true, words);
        }

        default void addNegativeSample(Word<I> word) {
            addSample(word, false);
        }

        default void addNegativeSamples(Collection<? extends Word<I>> words) {
            addSamples(false, words);
        }

        @SuppressWarnings("unchecked")
        default void addNegativeSamples(Word<I>... words) {
            addSamples(false, words);
        }
    }

}

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.api.algorithm;
17
18	import java.util.ArrayList;
19	import java.util.Arrays;
20	import java.util.Collection;
21	import java.util.Collections;
22	import java.util.List;
23
24	import de.learnlib.api.query.DefaultQuery;
25	import net.automatalib.automaton.fsa.DFA;
26	import net.automatalib.automaton.fsa.FiniteStateAcceptor;
27	import net.automatalib.automaton.fsa.NFA;
28	import net.automatalib.automaton.transducer.MealyMachine;
29	import net.automatalib.automaton.transducer.MooreMachine;
30	import net.automatalib.word.Word;
31
32	public interface PassiveLearningAlgorithm<M, I, D> {
33
34	void addSamples(Collection<? extends DefaultQuery<I, D>> samples);
35
36	@SuppressWarnings("unchecked")
37	default void addSamples(DefaultQuery<I, D>... samples) {
38	addSamples(Arrays.asList(samples));	×
39	}	×
40
41	@SuppressWarnings("unchecked")
42	default void addSamples(D output, Word<I>... words) {
43	addSamples(output, Arrays.asList(words));	1✔
44	}	1✔
45
46	default void addSamples(D output, Collection<? extends Word<I>> words) {
47	List<DefaultQuery<I, D>> queries = new ArrayList<>(words.size());	1✔
48	for (Word<I> word : words) {	1✔
49	queries.add(new DefaultQuery<>(word, output));	1✔
50	}	1✔
51
52	addSamples(queries);	1✔
53	}	1✔
54
55	default void addSample(Word<I> input, D output) {
56	addSample(new DefaultQuery<>(input, output));	1✔
57	}	1✔
58
59	default void addSample(DefaultQuery<I, D> sample) {
60	addSamples(Collections.singleton(sample));	1✔
61	}	1✔
62
63	/**
64	* Computes the model given the previously added samples.
65	* <p>
66	* <b>Implementation note:</b> It is up to the implementation if this operation is repeatable or not, An
67	* implementation may throw an {@link IllegalStateException} if additional samples are added after the first model
68	* construction.
69	*
70	* @return the computed model
71	*/
72	M computeModel();
73
74	/**
75	* Basic interface for passive learning algorithms that infer {@link DFA}s.
76	*
77	* @param <I>
78	* input symbol type
79	*/
80	interface PassiveDFALearner<I> extends PassiveAcceptorLearner<DFA<?, I>, I> {}
81
82	/**
83	* Basic interface for passive learning algorithms that infer {@link MealyMachine Mealy machines}.
84	*
85	* @param <I>
86	* input symbol type
87	* @param <O>
88	* output symbol type
89	*/
90	interface PassiveMealyLearner<I, O> extends PassiveLearningAlgorithm<MealyMachine<?, I, ?, O>, I, Word<O>> {}
91
92	/**
93	* Basic interface for passive learning algorithms that infer {@link MooreMachine Moore machines}.
94	*
95	* @param <I>
96	* input symbol type
97	* @param <O>
98	* output symbol type
99	*/
100	interface PassiveMooreLearner<I, O> extends PassiveLearningAlgorithm<MooreMachine<?, I, ?, O>, I, Word<O>> {}
101
102	/**
103	* Basic interface for passive learning algorithms that infer finite-state acceptors ({@link DFA}s or {@link
104	* NFA}s).
105	*
106	* @param <M>
107	* model type
108	* @param <I>
109	* input symbol type
110	*/
111	interface PassiveAcceptorLearner<M extends FiniteStateAcceptor<?, I>, I>
112	extends PassiveLearningAlgorithm<M, I, Boolean> {
113
114	default void addPositiveSample(Word<I> word) {
115	addSample(word, true);	1✔
116	}	1✔
117
118	default void addPositiveSamples(Collection<? extends Word<I>> words) {
119	addSamples(true, words);	×
120	}	×
121
122	@SuppressWarnings("unchecked")
123	default void addPositiveSamples(Word<I>... words) {
124	addSamples(true, words);	1✔
125	}	1✔
126
127	default void addNegativeSample(Word<I> word) {
128	addSample(word, false);	×
129	}	×
130
131	default void addNegativeSamples(Collection<? extends Word<I>> words) {
132	addSamples(false, words);	×
133	}	×
134
135	@SuppressWarnings("unchecked")
136	default void addNegativeSamples(Word<I>... words) {
137	addSamples(false, words);	1✔
138	}	1✔
139	}
140
141	}

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