add Moore variant

CHANGELOG.md

@@ -11,6 +11,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
 * Added the OSTIA passive learning algorithm, thanks to [Aleksander Mendoza-Drosik](https://github.com/aleksander-mendoza).
 * Added the OML (optimal-MAT-learner) active learning algorithm, thanks to [Falk Howar](https://github.com/fhowar).
 * Added a new learning algorithm for systems of procedural automata (SPAs).
+* Added Moore versions of the learners `DT`, `TTT`, `LStar`, thanks to [Mohamad Bayram](https://github.com/mohbayram).
 
 ### Changed
 
@@ -21,6 +22,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
 * The `ADT` class is no longer initialized with a `leafSplitter` but the `extendLeaf` and `splitLeaf` methods take an additional argument. This allows for a more customizable behavior.
 * The `{DFA,Mealy}CacheOracle`s and the `SULCache` are no longer thread-safe because the intended pipeline of a parallel setup (as suggested by the LearnLib factory methods) consists of a single-threaded cache that delegates to parallel (non-cached) oracles. Here, the synchronization logic only adds unnecessary overhead. In case you want a shared, thread-safe cache (which was currently not conveniently possible to setup) the `learnlib-parallelism` module now contains the `ThreadSafe{DFA,Mealy,SUL}Caches` factories which allow one to construct parallel oracles (whose parameters and return types are tailored towards using our `ParallelOracleBuilders` factory) with a shared cache. See the in-tree `ParallelismExample2` for reference.
 * `SymbolQueryCache` now needs to be created via the `MealyCaches` factory.
+* `AbstractTTTHypothesis` has received an additional type parameter for its state type.
 
 
 ### Removed

README.md

@@ -17,17 +17,17 @@ While certain features have been stripped for improved modularity, development h
 Currently, the following learning algorithms with respective target models are supported:
 
 
-Algorithm (active)  | Target models        || Algorithm (passive) | Models
+Algorithm (active)  | Target models                || Algorithm (passive) | Models
 --- | --- | --- | --- | ---
-ADT                 | `Mealy`              || OSTIA               | `SST`
-DHC                 | `Mealy`              || RPNI                | `DFA` `Mealy`
-Discrimination Tree | `DFA` `Mealy` `VPDA` || RPNI (EDSM)         | `DFA`
-Kearns & Vazirani   | `DFA` `Mealy`        || RPNI (MDL)          | `DFA`
-L* (incl. variants) | `DFA` `Mealy`
+ADT                 | `Mealy`                      || OSTIA               | `SST`
+DHC                 | `Mealy`                      || RPNI                | `DFA` `Mealy`
+Discrimination Tree | `DFA` `Mealy` `Moore` `VPDA` || RPNI (EDSM)         | `DFA`
+Kearns & Vazirani   | `DFA` `Mealy`                || RPNI (MDL)          | `DFA`
+L* (incl. variants) | `DFA` `Mealy` `Moore`
 NL*                 | `NFA`
 OML                 | `DFA` `Mealy`
 SPA                 | `SPA`
-TTT                 | `DFA` `Mealy` `VPDA`
+TTT                 | `DFA` `Mealy` `Moore` `VPDA`
 
 
 Additionally, LearnLib offers a variety of tools to ease the practical application of automata learning on real-world systems.

algorithms/active/discrimination-tree/src/main/java/de/learnlib/algorithms/discriminationtree/moore/DTLearnerMoore.java

@@ -0,0 +1,87 @@
+/* Copyright (C) 2013-2022 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.discriminationtree.moore;
+
+import com.github.misberner.buildergen.annotations.GenerateBuilder;
+import de.learnlib.algorithms.discriminationtree.AbstractDTLearner;
+import de.learnlib.algorithms.discriminationtree.DTLearnerState;
+import de.learnlib.algorithms.discriminationtree.hypothesis.HState;
+import de.learnlib.algorithms.discriminationtree.hypothesis.HTransition;
+import de.learnlib.api.algorithm.LearningAlgorithm.MooreLearner;
+import de.learnlib.api.oracle.MembershipOracle;
+import de.learnlib.api.query.AbstractQuery;
+import de.learnlib.api.query.Query;
+import de.learnlib.counterexamples.LocalSuffixFinder;
+import de.learnlib.datastructure.discriminationtree.MultiDTree;
+import net.automatalib.automata.transducers.MooreMachine;
+import net.automatalib.words.Alphabet;
+import net.automatalib.words.Word;
+import org.checkerframework.checker.nullness.qual.Nullable;
+
+/**
+ * A {@link MooreMachine}-based specialization of the DT learner.
+ *
+ * @param <I>
+ *         input symbol type
+ * @param <O>
+ *         output symbol type
+ *
+ * @author bayram
+ * @author frohme
+ */
+public class DTLearnerMoore<I, O> extends AbstractDTLearner<MooreMachine<?, I, ?, O>, I, Word<O>, O, Void>
+        implements MooreLearner<I, O> {
+
+    private HypothesisWrapperMoore<I, O> hypWrapper;
+
+    @GenerateBuilder(defaults = AbstractDTLearner.BuilderDefaults.class)
+    public DTLearnerMoore(Alphabet<I> alphabet,
+                          MembershipOracle<I, Word<O>> oracle,
+                          LocalSuffixFinder<? super I, ? super Word<O>> suffixFinder,
+                          boolean repeatedCounterexampleEvaluation) {
+
+        super(alphabet, oracle, suffixFinder, repeatedCounterexampleEvaluation, new MultiDTree<>(oracle));
+        this.hypWrapper = new HypothesisWrapperMoore<>(getHypothesisDS());
+
+    }
+
+    @Override
+    protected @Nullable Query<I, Word<O>> spQuery(HState<I, Word<O>, O, Void> state) {
+        return new AbstractQuery<I, Word<O>>(state.getAccessSequence(), Word.epsilon()) {
+
+            @Override
+            public void answer(Word<O> output) {
+                state.setProperty(output.firstSymbol());
+            }
+        };
+    }
+
+    @Override
+    protected @Nullable Query<I, Word<O>> tpQuery(HTransition<I, Word<O>, O, Void> transition) {
+        return null;
+    }
+
+    @Override
+    public MooreMachine<?, I, ?, O> getHypothesisModel() {
+        return hypWrapper;
+    }
+
+    @Override
+    public void resume(DTLearnerState<I, Word<O>, O, Void> state) {
+        super.resume(state);
+        this.hypWrapper = new HypothesisWrapperMoore<>(getHypothesisDS());
+    }
+}

algorithms/active/discrimination-tree/src/main/java/de/learnlib/algorithms/discriminationtree/moore/HypothesisWrapperMoore.java

@@ -0,0 +1,71 @@
+/* Copyright (C) 2013-2022 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.discriminationtree.moore;
+
+import java.util.Collection;
+
+import de.learnlib.algorithms.discriminationtree.hypothesis.DTLearnerHypothesis;
+import de.learnlib.algorithms.discriminationtree.hypothesis.HState;
+import de.learnlib.algorithms.discriminationtree.hypothesis.HTransition;
+import net.automatalib.automata.transducers.MooreMachine;
+import net.automatalib.words.Word;
+import org.checkerframework.checker.nullness.qual.Nullable;
+
+/**
+ * A {@link MooreMachine}-based specialization of the DT learner hypothesis.
+ *
+ * @param <I>
+ *         input symbol type
+ * @param <O>
+ *         output symbol type
+ *
+ * @author bayram
+ * @author frohme
+ */
+public class HypothesisWrapperMoore<I, O>
+        implements MooreMachine<HState<I, Word<O>, O, Void>, I, HTransition<I, Word<O>, O, Void>, O> {
+
+    private final DTLearnerHypothesis<I, Word<O>, O, Void> dtHypothesis;
+
+    HypothesisWrapperMoore(DTLearnerHypothesis<I, Word<O>, O, Void> dtHypothesis) {
+        this.dtHypothesis = dtHypothesis;
+    }
+
+    @Override
+    public O getStateOutput(HState<I, Word<O>, O, Void> state) {
+        return state.getProperty();
+    }
+
+    @Override
+    public Collection<HState<I, Word<O>, O, Void>> getStates() {
+        return dtHypothesis.getStates();
+    }
+
+    @Override
+    public @Nullable HState<I, Word<O>, O, Void> getInitialState() {
+        return dtHypothesis.getInitialState();
+    }
+
+    @Override
+    public @Nullable HTransition<I, Word<O>, O, Void> getTransition(HState<I, Word<O>, O, Void> state, I input) {
+        return dtHypothesis.getTransition(state, input);
+    }
+
+    @Override
+    public HState<I, Word<O>, O, Void> getSuccessor(HTransition<I, Word<O>, O, Void> transition) {
+        return dtHypothesis.getSuccessor(transition);
+    }
+}

algorithms/active/discrimination-tree/src/test/java/de/learnlib/algorithms/discriminationtree/DTLearnerMooreGrowingAlphabetTest.java

@@ -0,0 +1,36 @@
+/* Copyright (C) 2013-2022 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.discriminationtree;
+
+import de.learnlib.algorithms.discriminationtree.moore.DTLearnerMoore;
+import de.learnlib.api.oracle.MembershipOracle;
+import de.learnlib.counterexamples.LocalSuffixFinders;
+import de.learnlib.testsupport.AbstractGrowingAlphabetMooreTest;
+import net.automatalib.words.Alphabet;
+import net.automatalib.words.Word;
+
+/**
+ * @author frohme
+ */
+public class DTLearnerMooreGrowingAlphabetTest
+        extends AbstractGrowingAlphabetMooreTest<DTLearnerMoore<Character, Character>> {
+
+    @Override
+    protected DTLearnerMoore<Character, Character> getLearner(MembershipOracle<Character, Word<Character>> oracle,
+                                                              Alphabet<Character> alphabet) {
+        return new DTLearnerMoore<>(alphabet, oracle, LocalSuffixFinders.RIVEST_SCHAPIRE, true);
+    }
+}

algorithms/active/discrimination-tree/src/test/java/de/learnlib/algorithms/discriminationtree/DTLearnerMooreIT.java

@@ -0,0 +1,47 @@
+/* Copyright (C) 2013-2022 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.discriminationtree;
+
+import de.learnlib.algorithms.discriminationtree.moore.DTLearnerMooreBuilder;
+import de.learnlib.api.oracle.MembershipOracle.MooreMembershipOracle;
+import de.learnlib.counterexamples.LocalSuffixFinder;
+import de.learnlib.counterexamples.LocalSuffixFinders;
+import de.learnlib.testsupport.it.learner.AbstractMooreLearnerIT;
+import de.learnlib.testsupport.it.learner.LearnerVariantList.MooreLearnerVariantList;
+import net.automatalib.words.Alphabet;
+import net.automatalib.words.Word;
+import org.testng.annotations.Test;
+
+@Test
+public class DTLearnerMooreIT extends AbstractMooreLearnerIT {
+
+    @Override
+    protected <I, O> void addLearnerVariants(Alphabet<I> alphabet,
+                                             MooreMembershipOracle<I, O> mqOracle,
+                                             MooreLearnerVariantList<I, O> variants) {
+        DTLearnerMooreBuilder<I, O> builder = new DTLearnerMooreBuilder<>();
+        builder.setAlphabet(alphabet);
+        builder.setOracle(mqOracle);
+
+        for (LocalSuffixFinder<? super I, ? super Word<O>> suffixFinder : LocalSuffixFinders.values()) {
+            builder.setSuffixFinder(suffixFinder);
+
+            String name = "suffixFinder=" + suffixFinder.toString();
+            variants.addLearnerVariant(name, builder.create());
+        }
+    }
+
+}

algorithms/active/discrimination-tree/src/test/java/de/learnlib/algorithms/discriminationtree/DTLearnerMooreResumableLearnerTest.java

@@ -0,0 +1,41 @@
+/* Copyright (C) 2013-2022 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.discriminationtree;
+
+import de.learnlib.algorithms.discriminationtree.moore.DTLearnerMoore;
+import de.learnlib.algorithms.discriminationtree.moore.DTLearnerMooreBuilder;
+import de.learnlib.api.oracle.MembershipOracle;
+import de.learnlib.testsupport.AbstractResumableLearnerMooreTest;
+import net.automatalib.words.Alphabet;
+import net.automatalib.words.Word;
+
+/**
+ * @author frohme
+ */
+public class DTLearnerMooreResumableLearnerTest
+        extends AbstractResumableLearnerMooreTest<DTLearnerMoore<Character, Character>, DTLearnerState<Character, Word<Character>, Character, Void>> {
+
+    @Override
+    protected DTLearnerMoore<Character, Character> getLearner(final MembershipOracle<Character, Word<Character>> oracle,
+                                                              final Alphabet<Character> alphabet) {
+        return new DTLearnerMooreBuilder<Character, Character>().withAlphabet(alphabet).withOracle(oracle).create();
+    }
+
+    @Override
+    protected int getRounds() {
+        return 5;
+    }
+}