private TransformationChooser setUpReductionTransformer() {
ChainingIterable<VCTransformer> steps = new ChainingIterable<VCTransformer>();
SubstitutionRuleNormalizer normalizer = new SubstitutionRuleNormalizer(myTyper, false);
for (PExp e : myPExpTheorems) {
steps.add(normalizer.normalize(e));
}
return new NoBacktrackChooser(
new ProductiveStepChooser(
new UpfrontFitnessTransformationChooser(
new NormalizingTransformerFitnessFunction(),
steps,
0,
myTyper,
myInstanceEnvironment)));
}
private VCProver setUpProverDebug() {
ChainingIterable<VCTransformer> steps = new ChainingIterable<VCTransformer>();
steps.add(new ChooserEncapsulationStep("Reduce", setUpReductionTransformer()));
steps.add(new ExistentialInstantiationStep(myPExpTheorems));
SubstitutionRuleNormalizer normalizer = new SubstitutionRuleNormalizer(myTyper, false);
for (PExp e : myPExpTheorems) {
steps.add(normalizer.normalize(e));
}
Antecedent antecedent;
Consequent consequent;
for (Implication i : myImplications) {
antecedent = new Antecedent(i.getAntecedent(), myTyper);
consequent = new Consequent(i.getConsequent(), myTyper);
steps.add(new ConsequentWeakeningStep(antecedent, consequent));
steps.add(new TheoryDevelopingStep(antecedent, consequent, myPExpTheorems));
}
VCTransformer batchDeveloper = buildBatchTheoryDeveloper(5);
return new AlternativeProver(
myInstanceEnvironment,
new FirstStepGivenTransformationChooser(
new SimplifyingTransformationChooser(
new GuidedTransformationChooser(steps, myTyper), 0),
batchDeveloper),
myTyper);
}
