Sparse Learner

algorithms/active/pom.xml

@@ -43,6 +43,7 @@ limitations under the License.
         <module>observation-pack</module>
         <module>observation-pack-vpa</module>
         <module>procedural</module>
+        <module>sparse</module>
         <module>ttt</module>
         <module>ttt-vpa</module>
     </modules>

algorithms/active/sparse/pom.xml

@@ -0,0 +1,81 @@
+<?xml version="1.0"?>
+<!--
+Copyright (C) 2013-2025 TU Dortmund University
+This file is part of LearnLib <https://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.
+-->
+<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">
+    <modelVersion>4.0.0</modelVersion>
+
+    <parent>
+        <groupId>de.learnlib</groupId>
+        <artifactId>learnlib-algorithms-active-parent</artifactId>
+        <version>0.19.0-SNAPSHOT</version>
+        <relativePath>../pom.xml</relativePath>
+    </parent>
+
+    <artifactId>learnlib-sparse</artifactId>
+
+    <name>LearnLib :: Algorithms :: Sparse</name>
+    <description>
+        This artifact provides the implementation of the Sparse OT learning algorithm as described in the paper "Learning Mealy Machines with Sparse Observation Tables".
+    </description>
+
+    <dependencies>
+        <dependency>
+            <groupId>net.automatalib</groupId>
+            <artifactId>automata-api</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>net.automatalib</groupId>
+            <artifactId>automata-commons-util</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>net.automatalib</groupId>
+            <artifactId>automata-core</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>net.automatalib</groupId>
+            <artifactId>automata-util</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>de.learnlib</groupId>
+            <artifactId>learnlib-api</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>de.learnlib</groupId>
+            <artifactId>learnlib-counterexamples</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>de.learnlib</groupId>
+            <artifactId>learnlib-membership-oracles</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>de.learnlib</groupId>
+            <artifactId>learnlib-util</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>de.learnlib.testsupport</groupId>
+            <artifactId>learnlib-learner-it-support</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>net.automatalib</groupId>
+            <artifactId>automata-serialization-dot</artifactId>
+        </dependency>
+        <dependency>
+            <groupId>org.testng</groupId>
+            <artifactId>testng</artifactId>
+        </dependency>
+    </dependencies>
+</project>

algorithms/active/sparse/src/main/java/de/learnlib/algorithm/sparse/CoreRow.java

@@ -0,0 +1,43 @@
+/* Copyright (C) 2013-2025 TU Dortmund University
+ * This file is part of LearnLib <https://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.sparse;
+
+import java.util.HashMap;
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Set;
+
+import net.automatalib.word.Word;
+
+class CoreRow<S, I, O> extends Row<S, I, O> {
+    final S state; // hypothesis state associated with this row
+    final int idx; // index in core row list
+    final Map<Word<I>, Word<O>> sufToOut; // maps suffixes to the outputs contained in this row
+    final Set<Integer> cellIds; // also store identifiers of suffix-output pairs for fast compatability checking
+
+    CoreRow(Word<I> prefix, S state, int idx) {
+        super(prefix);
+        this.state = state;
+        this.idx = idx;
+        sufToOut = new HashMap<>();
+        cellIds = new HashSet<>(); // use HashSet to enable fast containment checks
+    }
+
+    void addSuffix(Word<I> suf, Word<O> out, int cell) {
+        sufToOut.put(suf, out);
+        cellIds.add(cell);
+    }
+}

algorithms/active/sparse/src/main/java/de/learnlib/algorithm/sparse/FringeRow.java

@@ -0,0 +1,37 @@
+/* Copyright (C) 2013-2025 TU Dortmund University
+ * This file is part of LearnLib <https://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.sparse;
+
+import net.automatalib.word.Word;
+
+class FringeRow<S, I, O> extends Row<S, I, O> {
+
+    // each fringe row represents a hypothesis transition
+    final S srcState; // source state
+    final I transIn; // input symbol
+    O transOut; // output symbol (determined dynamically)
+    Leaf<S, I, O> leaf;
+    // for compression, fringe rows do not store observations directly.
+    // instead, they point to some leaf in a tree encoding their classification history.
+    // this trick avoids redundantly storing identical observations.
+
+    FringeRow(Word<I> prefix, S srcState, Leaf<S, I, O> leaf) {
+        super(prefix);
+        this.srcState = srcState;
+        this.transIn = prefix.lastSymbol();
+        this.leaf = leaf;
+    }
+}