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‎.gitignore

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# Python virtualenv
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venv/
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# Maven output
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target/
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# Eclipse output directory
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bin/
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# Eclipse settings
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.settings/
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.classpath
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.project
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.factorypath
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#Intellij settings
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*.iml
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.idea/

‎java/pom.xml

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<?xml version="1.0" encoding="UTF-8" ?>
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<!--
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Copyright (C) 2013-2018 TU Dortmund
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This file is part of LearnLib, http://www.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:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://maven.apache.org/POM/4.0.0"
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xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
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<modelVersion>4.0.0</modelVersion>
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<groupId>com.github.mtf90</groupId>
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<artifactId>learnlib-py4j-example</artifactId>
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<version>1.0-SNAPSHOT</version>
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<packaging>jar</packaging>
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<properties>
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<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
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<!-- AutomataLib requires Java 8 -->
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<maven.compiler.source>1.8</maven.compiler.source>
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<maven.compiler.target>1.8</maven.compiler.target>
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<!-- Version of LearnLib to use -->
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<learnlib.version>0.13.1</learnlib.version>
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</properties>
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<dependencyManagement>
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<dependencies>
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<dependency>
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<groupId>de.learnlib</groupId>
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<artifactId>learnlib-parent</artifactId>
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<version>${learnlib.version}</version>
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<type>pom</type>
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<scope>import</scope>
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</dependency>
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</dependencies>
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</dependencyManagement>
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<dependencies>
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<dependency>
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<groupId>de.learnlib.distribution</groupId>
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<artifactId>learnlib-distribution</artifactId>
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<type>pom</type>
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</dependency>
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<dependency>
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<groupId>net.sf.py4j</groupId>
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<artifactId>py4j</artifactId>
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<version>0.10.8.1</version>
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</dependency>
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<!-- provide an SLF4J implementation -->
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<dependency>
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<groupId>ch.qos.logback</groupId>
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<artifactId>logback-classic</artifactId>
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<scope>runtime</scope>
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</dependency>
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</dependencies>
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<build>
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<plugins>
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<plugin>
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<groupId>org.apache.maven.plugins</groupId>
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<artifactId>maven-shade-plugin</artifactId>
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<version>3.2.1</version>
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<executions>
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<execution>
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<phase>package</phase>
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<goals>
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<goal>shade</goal>
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</goals>
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<configuration>
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<createDependencyReducedPom>false</createDependencyReducedPom>
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<transformers>
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<transformer implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer"/>
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<transformer implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
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<mainClass>com.github.mtf90.Main</mainClass>
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</transformer>
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</transformers>
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</configuration>
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</execution>
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</executions>
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</plugin>
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</plugins>
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</build>
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</project>
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‎java/src/main/java/com/github/mtf90/Main.java

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package com.github.mtf90;
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import py4j.GatewayServer;
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public class Main {
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public static void main(String[] args) {
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GatewayServer server = new GatewayServer();
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server.start();
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}
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}

‎python/Main.py

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from py4j.java_gateway import JavaGateway, CallbackServerParameters
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class PySUL:
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def __init__(self, gateway):
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self.alphabet = gateway.jvm.net.automatalib.words.impl.Alphabets.characters('a', 'b')
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self.state = 0
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def pre(self):
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self.state = 0
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def post(self): pass
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def step(self, sulInput):
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if sulInput == 'b':
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self.state = (self.state + 1) % 2
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return 'b'
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return '0' if self.state == 0 else '1'
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def canFork(self):
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return False
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def fork(self): pass
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class Java:
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implements = ["de.learnlib.api.SUL"]
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def main():
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gateway = JavaGateway(callback_server_parameters=CallbackServerParameters())
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sul = PySUL(gateway)
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alphabet = sul.alphabet
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mq_oracle = gateway.jvm.de.learnlib.oracle.membership.SULOracle(sul)
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eq_oracle = gateway.jvm.de.learnlib.oracle.equivalence.WMethodEQOracle(mq_oracle, 3)
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ttt = gateway.jvm.de.learnlib.algorithms.ttt.mealy.TTTLearnerMealyBuilder() \
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.withAlphabet(alphabet) \
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.withOracle(mq_oracle) \
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.create()
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experiment = gateway.jvm.de.learnlib.util.Experiment(ttt, eq_oracle, alphabet)
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experiment.run()
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hyp = experiment.getFinalHypothesis()
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string_writer = gateway.jvm.java.io.StringWriter()
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gateway.jvm.net.automatalib.serialization.dot.GraphDOT.write(hyp, alphabet, string_writer,
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# While varargs allow us to skip this parameter in Java, the method signature expects an array \
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gateway.new_array(
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gateway.jvm.net.automatalib.serialization.dot.DOTVisualizationHelper,
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0))
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print("Learned model in DOT format:")
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print()
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print(string_writer.toString())
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gateway.jvm.net.automatalib.visualization.Visualization.visualize(hyp, alphabet,
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# While varargs allow us to skip this parameter in Java, the method signature expects an array \
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gateway.new_array(
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gateway.jvm.net.automatalib.visualization.VisualizationHelper,
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0))
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gateway.close()
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if __name__ == "__main__":
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main()

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