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tiferrei
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L# Algorithm (#141)
* feat: lsharp * fix: LSoracle Rule3 SepSeq mode * fix: tidy pom * chore: tidy imports * chore: spotbugs * chore: spotbugs * chore: spotbugs * chore: spotbugs * chore: spotbugs * chore: pmd * chore: pmd * chore: pmd * chore: pmd * chore: pmd * chore: pmd * chore: checkstyle * chore: checkstyle * chore: checkstyle * chore: checkstyle * fix: use SymbolQueryOracle instead of MembershipOracle in LSharp Thanks to @stateMachinist for noticing this issue and providing us with a patch. Co-authored-by: stateMachinist * chore: update CI * chore: update CI * chore: remove L# test. I couldn't get it to work with MealyIT given the use of the SymbolQueryOracle. * update to latest refactorings * restore old integration test * initial cleanup drop dead code and make code analysis plugins happy * replace LSMealyMachine with CompactMealy * determinize integration tests * de-stream-ify code not having to deal with multithreading (and therefore not having to deal with synchronization) sped up integration tests by a factor of >30 * do not use exceptions for control flow * cleanup dependencies drop guava * fix issues reported by checkerframework * include into existing hierarchies * general cleanups * documentation * ignore LSharp builder in coverage * add comment detailing the scope of the implementation --------- Co-authored-by: Markus Frohme <mtf90@users.noreply.github.com> Co-authored-by: Markus Frohme <markus.frohme@udo.edu>
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‎CHANGELOG.md‎

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### Added
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* LearnLib now supports JPMS modules. All artifacts now provide a `module-info` descriptor except of the distribution artifacts (for Maven-less environments) which only provide an `Automatic-Module-Name` due to non-modular dependencies. Note that while this is a Java 9+ feature, LearnLib still supports Java 8 byte code for the remaining class files.
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* Added the L# active learning algorithm (thanks to [Tiago Ferreira](https://github.com/tiferrei)).
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* The `ADTLearner` has been refactored to no longer use the (now-removed) `SymbolQueryOracle` but a new `AdaptiveMembershipOracle` instead which supports answering queries in parallel (thanks to [Leon Vitorovic](https://github.com/leonthalee)).
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* Added an `InterningMembershipOracle` (including refinements) to the `learnlib-cache` artifact that interns query responses to reduce memory consumption of large data structures. This exports the internal concepts of the DHC learner (which no longer interns query responses automatically).
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* `StaticParallelOracleBuilder` now supports custom executor services.

‎README.md‎

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| DHC | `Mealy` | | | |
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| Kearns & Vazirani | `DFA` `Mealy` | | | |
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| Lambda | `DFA` `Mealy` | | | |
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| L# | `Mealy` | | | |
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| L* (incl. variants) | `DFA` `Mealy` `Moore` | | | |
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| NL* | `NFA` | | | |
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| Observation Pack | `DFA` `Mealy` `Moore` `VPA` | | | |

‎algorithms/active/adt/src/test/java/de/learnlib/algorithm/adt/it/ADTIT.java‎

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import de.learnlib.oracle.membership.MealySimulatorOracle;
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import de.learnlib.oracle.membership.SULAdaptiveOracle;
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import de.learnlib.sul.SUL;
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import de.learnlib.testsupport.MQ2AQWrapper;
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import de.learnlib.testsupport.it.learner.AbstractMealyLearnerIT;
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import de.learnlib.testsupport.it.learner.LearnerVariantList;
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import de.learnlib.util.Experiment.MealyExperiment;

‎algorithms/active/lsharp/pom.xml‎

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<?xml version="1.0"?>
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<!--
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Copyright (C) 2013-2025 TU Dortmund University
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This file is part of LearnLib <https://learnlib.de>.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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-->
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<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">
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<modelVersion>4.0.0</modelVersion>
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<parent>
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<groupId>de.learnlib</groupId>
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<artifactId>learnlib-algorithms-active-parent</artifactId>
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<version>0.18.0-SNAPSHOT</version>
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<relativePath>../pom.xml</relativePath>
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</parent>
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<artifactId>learnlib-lsharp</artifactId>
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<name>LearnLib :: Algorithms :: L#</name>
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<description>
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This artifact provides the implementation of the L# algorithm as described in the paper "A New Approach for
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Active Automata Learning Based on Apartness" (https://doi.org/10.1007/978-3-030-99524-9_12) by Frits Vaandrager,
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Bharat Garhewal, Jurriaan Rot, and Thorsten Wißmann.
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</description>
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<dependencies>
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<!-- internal -->
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<dependency>
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<groupId>de.learnlib</groupId>
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<artifactId>learnlib-api</artifactId>
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</dependency>
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<dependency>
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<groupId>de.learnlib</groupId>
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<artifactId>learnlib-util</artifactId>
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</dependency>
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<!-- external -->
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<dependency>
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<groupId>net.automatalib</groupId>
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<artifactId>automata-api</artifactId>
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</dependency>
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<dependency>
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<groupId>net.automatalib</groupId>
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<artifactId>automata-core</artifactId>
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</dependency>
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<dependency>
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<groupId>net.automatalib</groupId>
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<artifactId>automata-commons-util</artifactId>
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</dependency>
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<!-- build -->
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<dependency>
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<groupId>de.learnlib.tooling</groupId>
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<artifactId>annotations</artifactId>
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</dependency>
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<dependency>
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<groupId>org.checkerframework</groupId>
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<artifactId>checker-qual</artifactId>
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</dependency>
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<!-- test -->
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<dependency>
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<groupId>de.learnlib.testsupport</groupId>
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<artifactId>learnlib-learner-it-support</artifactId>
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</dependency>
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<dependency>
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<groupId>de.learnlib.testsupport</groupId>
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<artifactId>learnlib-test-support</artifactId>
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</dependency>
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<dependency>
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<groupId>net.automatalib</groupId>
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<artifactId>automata-serialization-dot</artifactId>
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<scope>test</scope>
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</dependency>
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<dependency>
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<groupId>org.testng</groupId>
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<artifactId>testng</artifactId>
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</dependency>
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</dependencies>
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</project>

‎algorithms/active/lsharp/src/main/java/de/learnlib/algorithm/lsharp/ApartnessUtil.java‎

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/* Copyright (C) 2013-2025 TU Dortmund University
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* This file is part of LearnLib <https://learnlib.de>.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package de.learnlib.algorithm.lsharp;
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import java.util.ArrayDeque;
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import java.util.Deque;
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import java.util.Objects;
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import net.automatalib.automaton.transducer.MealyMachine;
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import net.automatalib.common.util.Pair;
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import net.automatalib.word.Word;
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import org.checkerframework.checker.nullness.qual.NonNull;
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import org.checkerframework.checker.nullness.qual.Nullable;
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public final class ApartnessUtil {
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private ApartnessUtil() {
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// prevent instantiation
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}
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public static <S extends Comparable<S>, I, O> @Nullable Word<I> computeWitness(ObservationTree<S, I, O> tree,
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S s1,
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S s2) {
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S t = showsStatesAreApart(tree, s1, s2);
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if (t == null) {
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return null;
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}
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return tree.getTransferSeq(t, s1);
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}
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public static <S extends Comparable<S>, I, O> boolean statesAreApart(ObservationTree<S, I, O> tree, S s1, S s2) {
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return showsStatesAreApart(tree, s1, s2) != null;
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}
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public static <S extends Comparable<S>, I, O> boolean accStatesAreApart(ObservationTree<S, I, O> tree,
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Word<I> s1a,
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Word<I> s2a) {
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S s1 = tree.getSucc(tree.defaultState(), s1a);
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assert s1 != null;
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S s2 = tree.getSucc(tree.defaultState(), s2a);
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assert s2 != null;
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return statesAreApart(tree, s1, s2);
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}
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public static <S1 extends Comparable<S1>, S2, I, O> @Nullable Word<I> treeAndHypComputeWitness(ObservationTree<S1, I, O> tree,
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S1 st,
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MealyMachine<S2, I, ?, O> fsm,
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S2 sh) {
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S1 s = treeAndHypShowsStatesAreApart(tree, st, sh, fsm);
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if (s == null) {
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return null;
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}
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return tree.getTransferSeq(s, st);
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}
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public static <S1 extends Comparable<S1>, S2, I, O> @Nullable S1 treeAndHypShowsStatesAreApart(ObservationTree<S1, I, O> tree,
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S1 st,
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S2 sh,
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MealyMachine<S2, I, ?, O> fsm) {
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Deque<Pair<S1, S2>> queue = new ArrayDeque<>();
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queue.push(Pair.of(st, sh));
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while (!queue.isEmpty()) {
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@SuppressWarnings("nullness") // false positive https://github.com/typetools/checker-framework/issues/399
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@NonNull Pair<S1, S2> pair = queue.poll();
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S1 q = pair.getFirst();
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S2 r = pair.getSecond();
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for (I i : tree.getInputAlphabet()) {
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Pair<O, S1> stepFree = tree.getOutSucc(q, i);
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if (stepFree != null) {
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S2 dh = fsm.getSuccessor(r, i);
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assert dh != null;
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O outHyp = fsm.getOutput(r, i);
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assert outHyp != null;
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if (outHyp.equals(stepFree.getFirst())) {
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queue.push(Pair.of(stepFree.getSecond(), dh));
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} else {
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return stepFree.getSecond();
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}
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}
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}
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}
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return null;
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}
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private static <S extends Comparable<S>, I, O> @Nullable Pair<O, S> step(ObservationTree<S, I, O> tree, S x, I i) {
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return tree.getOutSucc(x, i);
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}
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private static <S extends Comparable<S>, I, O> @Nullable Pair<Pair<O, S>, Pair<O, S>> treeRespPairInput(
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ObservationTree<S, I, O> tree,
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S x,
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S y,
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I i) {
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Pair<O, S> s1 = step(tree, x, i);
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Pair<O, S> s2 = step(tree, y, i);
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if (s1 == null || s2 == null) {
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return null;
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}
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return Pair.of(s1, s2);
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}
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public static <S extends Comparable<S>, I, O> @Nullable S showsStatesAreApart(ObservationTree<S, I, O> tree,
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S s1,
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S s2) {
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Deque<Pair<S, S>> workList = new ArrayDeque<>();
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workList.add(Pair.of(s1, s2));
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while (!workList.isEmpty()) {
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Pair<S, S> pair = workList.pop();
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S fst = pair.getFirst();
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S snd = pair.getSecond();
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for (I i : tree.getInputAlphabet()) {
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Pair<Pair<O, S>, Pair<O, S>> p = treeRespPairInput(tree, fst, snd, i);
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if (p != null) {
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Pair<O, S> fstOD = p.getFirst();
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Pair<O, S> sndOD = p.getSecond();
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O fstO = fstOD.getFirst();
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S fstD = fstOD.getSecond();
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O sndO = sndOD.getFirst();
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S sndD = sndOD.getSecond();
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if (Objects.equals(fstO, sndO)) {
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workList.push(Pair.of(fstD, sndD));
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} else {
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return fstD;
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}
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}
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}
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}
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return null;
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}
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}

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