Package statechum.model.testset

Examples of statechum.model.testset.PTA_FSMStructure

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  @Test
  public final void test_stringCollectionSize0()
  {
    fsm = buildLearnerGraph("A-a->A-b->B", "test_sequenceSet3_6",mainConfiguration,converter);
    en = new PTA_FSMStructure(fsm,null);   
    SequenceSet seq = en.new SequenceSet();seq.setIdentity();
    vertifyPTA(en, 1, new String[][] {
        new String[] {}
    });
    int expectedCompressed = 0, expectedUncompressed = 0;
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  @Test
  public final void test_stringCollectionSize1()
  {
    fsm = buildLearnerGraph("A-a->A-b->B", "test_sequenceSet3_6",mainConfiguration,converter);
    en = new PTA_FSMStructure(fsm,null);   
    SequenceSet seq = en.new SequenceSet();seq.setIdentity();
    seq.crossWithSequence(labelList(new String[] {"b","a"}));
    vertifyPTA(en, 1, new String[][] {
        new String[] {"b","a"}
    });
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  @Test
  public final void test_stringCollectionSize2()
  {
    fsm = buildLearnerGraph("A-a->A-b->B", "test_sequenceSet3_6",mainConfiguration,converter);
    en = new PTA_FSMStructure(fsm,null);   
    SequenceSet seq = en.new SequenceSet();seq.setIdentity();
    seq.crossWithSet(labelList(new String[] {"b","a"}))
      .crossWithSet(labelList(new String[] {"b","a"}))
      .crossWithSet(labelList(new String[] {"a","b"}));
    vertifyPTA(en, 6, new String[][] {
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  @Before
  public final void setUp()
  {
    mainConfiguration.setAllowedToCloneNonCmpVertex(true);
    fsm = buildLearnerGraph("A-a->B-a->A-b-#C\nB-b->D-c->E", "TestPTATestSequenceEngine",mainConfiguration,converter);
    en = new PTA_FSMStructure(fsm,null);   
    engine_testLimitToGraph = new PTA_FSMStructure(buildLearnerGraph(
        "A-a->B-a->F-b-#C\nB-c->D\nA-c->A\nB-b->D-c->E", "TestPTATestSequenceEngine",mainConfiguration,converter),null);
    //Visualiser.updateFrame(buildLearnerGraph(
    //    "A-a->B-a->F-b-#C\nB-c->D\nA-c->A\nB-b->D-c->E", "TestPTATestSequenceEngine",config), null);
    //Visualiser.waitForKey();
  }
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    DirectedSparseVertex init = new DirectedSparseVertex();
    init.addUserDatum(JUConstants.INITIAL, true, UserData.SHARED);
    init.addUserDatum(JUConstants.ACCEPTED, false, UserData.SHARED);
    init.addUserDatum(JUConstants.LABEL, "A", UserData.SHARED);
    g.addVertex(init);
    PTASequenceEngine enVerySmall = new PTA_FSMStructure(new LearnerGraph(g,mainConfiguration),null);
    vertifyPTA(enVerySmall, 1, new String[][] {
        new String[] {}
      });
  }
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    DirectedSparseVertex init = new DirectedSparseVertex();
    init.addUserDatum(JUConstants.INITIAL, true,UserData.SHARED);
    init.addUserDatum(JUConstants.ACCEPTED, true, UserData.SHARED);
    init.addUserDatum(JUConstants.LABEL, "A", UserData.SHARED);
    g.addVertex(init);
    PTASequenceEngine enVerySmall = new PTA_FSMStructure(new LearnerGraph(g,mainConfiguration),null);
    vertifyPTA(enVerySmall, 1, new String[][] {
        new String[] {}
    });
  }
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  @Test
  public final void test_sequenceSet3_5() // a more complex composition
  {
    fsm = buildLearnerGraph("A-a->B-a->A-b-#C\nA-d->M-a->N\nB-b->D-c->E", "test_sequenceSet3_5",mainConfiguration,converter);
    en = new PTA_FSMStructure(fsm,null);   
    SequenceSet seq = en.new SequenceSet();seq.setIdentity();
    SequenceSet temp2 = seq.crossWithSet(labelList(new String[] {"b","a","d"}))
      .crossWithSet(labelList(new String[] {"b","a","d"}));
    Map<String,String> actual2 = getDebugDataMap(en,temp2.crossWithSet(labelList(new String[] {"a"})));
    Map<String,String> actual1 = getDebugDataMap(en,temp2);
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  @Test
  public final void test_sequenceSet3_6() // a more complex composition
  {
    fsm = buildLearnerGraph("A-a->A-b->B", "test_sequenceSet3_6",mainConfiguration,converter);
    en = new PTA_FSMStructure(fsm,null);   
    SequenceSet seq = en.new SequenceSet();seq.setIdentity();
    Map<String,String> actual = getDebugDataMap(en,seq.crossWithSet(labelList(new String[] {"b","a"}))
      .crossWithSet(labelList(new String[] {"b","a"}))
      .crossWithSet(labelList(new String[] {"a","b"})));
    vertifyPTA(en, 6, new String[][] {
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  /** Test that it is possible to selectively filter out paths which terminate at specific states. */
  @Test
  public final void test_sequenceSet_testing_shouldBeReturned1() // a test for shouldBeReturned
  {
    final LearnerGraph machine = buildLearnerGraph("A-a->A-b->B", "test_sequenceSet_testing_shouldBeReturned1",mainConfiguration,converter);
    en = new PTA_FSMStructure(machine,null) {
      {
        init(machine.new FSMImplementation(){
          @Override
          public boolean shouldBeReturned(Object elem) {
            // elem is null for REJECT states
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  /** Test that the outcome of filter is not affected by subsequent changes in the original graph. */
  @Test
  public final void test_sequenceSet_testing_shouldBeReturned_filter_is_a_copy()
  {
    final LearnerGraph machine = buildLearnerGraph("A-a->A-b->B-b->B\nA-d->A\nB-c->D-a->D", "test_sequenceSet_testing_shouldBeReturned_filter_is_a_copy",mainConfiguration,converter);
    en = new PTA_FSMStructure(machine,null) {
      {
        init(machine.new FSMImplementation(){
          @Override
          public boolean shouldBeReturned(Object elem) {
            // elem is null for REJECT states
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Related Classes of statechum.model.testset.PTA_FSMStructure

  • statechum.analysis.learning.experiments.Benchmarklinear
  • statechum.analysis.learning.experiments.CompareGraphs
  • statechum.analysis.learning.experiments.IncrementalAccuracyAndQuestionsExperiment$RPNIEvaluator
  • statechum.analysis.learning.experiments.StructuralDifferencesPaper
  • statechum.analysis.learning.rpnicore.WMethod
  • statechum.apps.CompareGraphs
  • statechum.model.testset.TestPTA_computePrecisionRecall
  • statechum.model.testset.TestPTASequenceEngine
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