procedural: add OptimalLStar adapters

algorithms/active/oml/src/main/java/de/learnlib/algorithm/oml/lstar/AbstractOptimalLStar.java

@@ -72,7 +72,7 @@ abstract class AbstractOptimalLStar<M extends SuffixOutput<I, D>, I, D> implemen
 
     abstract boolean symbolInconsistency(Word<I> u1, Word<I> u2, I a);
 
-    abstract List<D> rowForState(Word<I> input);
+    protected abstract List<D> rowForState(Word<I> input);
 
     @Override
     public void startLearning() {
@@ -218,7 +218,7 @@ private List<Word<I>> getShortPrefixes(Word<I> prefix) {
         return getShortPrefixes(rowData);
     }
 
-    List<Word<I>> getShortPrefixes(List<D> rowData) {
+    protected List<Word<I>> getShortPrefixes(List<D> rowData) {
         List<Word<I>> shortReps = new ArrayList<>();
         for (Entry<Word<I>, List<D>> e : rows.entrySet()) {
             if (shortPrefixes.contains(e.getKey()) && rowData.equals(e.getValue())) {

algorithms/active/oml/src/main/java/de/learnlib/algorithm/oml/lstar/OptimalLStarDFA.java

@@ -93,7 +93,7 @@ public int size() {
     }
 
     @Override
-    public List<Boolean> rowForState(Word<I> input) {
+    protected List<Boolean> rowForState(Word<I> input) {
         return hypStateMap.get(hypothesis.getState(input));
     }
 

algorithms/active/oml/src/main/java/de/learnlib/algorithm/oml/lstar/OptimalLStarMealy.java

@@ -51,7 +51,7 @@ public int size() {
     }
 
     @Override
-    public List<Word<O>> rowForState(Word<I> input) {
+    protected List<Word<O>> rowForState(Word<I> input) {
         return hypStateMap.get(hypothesis.getState(input));
     }
 

algorithms/active/procedural/src/main/java/de/learnlib/algorithm/procedural/adapter/dfa/OptimalLStarAdapterDFA.java

@@ -0,0 +1,47 @@
+/* Copyright (C) 2013-2024 TU Dortmund University
+ * 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.procedural.adapter.dfa;
+
+import java.util.List;
+
+import de.learnlib.AccessSequenceTransformer;
+import de.learnlib.algorithm.oml.lstar.OptimalLStarDFA;
+import de.learnlib.oracle.MembershipOracle;
+import net.automatalib.alphabet.Alphabet;
+import net.automatalib.word.Word;
+
+/**
+ * Adapter for using {@link OptimalLStarDFA} as a procedural learner.
+ *
+ * @param <I>
+ *         input symbol type
+ */
+public class OptimalLStarAdapterDFA<I> extends OptimalLStarDFA<I> implements AccessSequenceTransformer<I> {
+
+    public OptimalLStarAdapterDFA(Alphabet<I> alphabet, MembershipOracle<I, Boolean> oracle) {
+        super(alphabet, oracle);
+    }
+
+    @Override
+    public Word<I> transformAccessSequence(Word<I> word) {
+        final List<Boolean> row = super.rowForState(word);
+        final List<Word<I>> shortPrefixes = super.getShortPrefixes(row);
+
+        assert shortPrefixes.size() == 1;
+
+        return shortPrefixes.get(0);
+    }
+}

algorithms/active/procedural/src/main/java/de/learnlib/algorithm/procedural/adapter/mealy/OptimalLStarAdapterMealy.java

@@ -0,0 +1,49 @@
+/* Copyright (C) 2013-2024 TU Dortmund University
+ * 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.procedural.adapter.mealy;
+
+import java.util.List;
+
+import de.learnlib.AccessSequenceTransformer;
+import de.learnlib.algorithm.oml.lstar.OptimalLStarMealy;
+import de.learnlib.oracle.MembershipOracle;
+import net.automatalib.alphabet.Alphabet;
+import net.automatalib.word.Word;
+
+/**
+ * Adapter for using {@link OptimalLStarMealy} as a procedural learner.
+ *
+ * @param <I>
+ *         input symbol type
+ * @param <O>
+ *         output symbol type
+ */
+public class OptimalLStarAdapterMealy<I, O> extends OptimalLStarMealy<I, O> implements AccessSequenceTransformer<I> {
+
+    public OptimalLStarAdapterMealy(Alphabet<I> alphabet, MembershipOracle<I, Word<O>> oracle) {
+        super(alphabet, oracle);
+    }
+
+    @Override
+    public Word<I> transformAccessSequence(Word<I> word) {
+        final List<Word<O>> row = super.rowForState(word);
+        final List<Word<I>> shortPrefixes = super.getShortPrefixes(row);
+
+        assert shortPrefixes.size() == 1;
+
+        return shortPrefixes.get(0);
+    }
+}

algorithms/active/procedural/src/test/java/de/learnlib/algorithm/procedural/sba/it/SBAIT.java

@@ -28,6 +28,7 @@
 import de.learnlib.algorithm.procedural.adapter.dfa.KearnsVaziraniAdapterDFA;
 import de.learnlib.algorithm.procedural.adapter.dfa.LStarBaseAdapterDFA;
 import de.learnlib.algorithm.procedural.adapter.dfa.ObservationPackAdapterDFA;
+import de.learnlib.algorithm.procedural.adapter.dfa.OptimalLStarAdapterDFA;
 import de.learnlib.algorithm.procedural.adapter.dfa.OptimalTTTAdapterDFA;
 import de.learnlib.algorithm.procedural.adapter.dfa.RivestSchapireAdapterDFA;
 import de.learnlib.algorithm.procedural.adapter.dfa.TTTAdapterDFA;
@@ -54,6 +55,7 @@ protected <I> void addLearnerVariants(ProceduralInputAlphabet<I> alphabet,
         builder.addLearnerVariant(KearnsVaziraniAdapterDFA::new);
         builder.addLearnerVariant(LStarBaseAdapterDFA::new);
         builder.addLearnerVariant(ObservationPackAdapterDFA::new);
+        builder.addLearnerVariant(OptimalLStarAdapterDFA::new);
         builder.addLearnerVariant(OptimalTTTAdapterDFA::new);
         builder.addLearnerVariant(RivestSchapireAdapterDFA::new);
         builder.addLearnerVariant(TTTAdapterDFA::new);

algorithms/active/procedural/src/test/java/de/learnlib/algorithm/procedural/spa/it/SPAIT.java

@@ -27,6 +27,7 @@
 import de.learnlib.algorithm.procedural.adapter.dfa.KearnsVaziraniAdapterDFA;
 import de.learnlib.algorithm.procedural.adapter.dfa.LStarBaseAdapterDFA;
 import de.learnlib.algorithm.procedural.adapter.dfa.ObservationPackAdapterDFA;
+import de.learnlib.algorithm.procedural.adapter.dfa.OptimalLStarAdapterDFA;
 import de.learnlib.algorithm.procedural.adapter.dfa.OptimalTTTAdapterDFA;
 import de.learnlib.algorithm.procedural.adapter.dfa.RivestSchapireAdapterDFA;
 import de.learnlib.algorithm.procedural.adapter.dfa.TTTAdapterDFA;
@@ -53,6 +54,7 @@ protected <I> void addLearnerVariants(ProceduralInputAlphabet<I> alphabet,
         builder.addLearnerVariant(KearnsVaziraniAdapterDFA::new);
         builder.addLearnerVariant(LStarBaseAdapterDFA::new);
         builder.addLearnerVariant(ObservationPackAdapterDFA::new);
+        builder.addLearnerVariant(OptimalLStarAdapterDFA::new);
         builder.addLearnerVariant(OptimalTTTAdapterDFA::new);
         builder.addLearnerVariant(RivestSchapireAdapterDFA::new);
         builder.addLearnerVariant(TTTAdapterDFA::new);

algorithms/active/procedural/src/test/java/de/learnlib/algorithm/procedural/spmm/it/SPMMIT.java

@@ -27,6 +27,7 @@
 import de.learnlib.algorithm.procedural.adapter.mealy.KearnsVaziraniAdapterMealy;
 import de.learnlib.algorithm.procedural.adapter.mealy.LStarBaseAdapterMealy;
 import de.learnlib.algorithm.procedural.adapter.mealy.ObservationPackAdapterMealy;
+import de.learnlib.algorithm.procedural.adapter.mealy.OptimalLStarAdapterMealy;
 import de.learnlib.algorithm.procedural.adapter.mealy.OptimalTTTAdapterMealy;
 import de.learnlib.algorithm.procedural.adapter.mealy.RivestSchapireAdapterMealy;
 import de.learnlib.algorithm.procedural.adapter.mealy.TTTAdapterMealy;
@@ -56,6 +57,7 @@ protected <I, O> void addLearnerVariants(ProceduralInputAlphabet<I> alphabet,
         builder.addLearnerVariant(LStarBaseAdapterMealy::new);
         builder.addLearnerVariant(MealyDHC::new);
         builder.addLearnerVariant(ObservationPackAdapterMealy::new);
+        builder.addLearnerVariant(OptimalLStarAdapterMealy::new);
         builder.addLearnerVariant(OptimalTTTAdapterMealy::new);
         builder.addLearnerVariant(RivestSchapireAdapterMealy::new);
         builder.addLearnerVariant(TTTAdapterMealy::new);