Module de.learnlib.algorithm.observationpack.vpa

Package de.learnlib.algorithm.observationpack.vpa

Class AbstractVPALearner<I>

java.lang.Object

de.learnlib.algorithm.observationpack.vpa.AbstractVPALearner<I>

All Implemented Interfaces:

LearningAlgorithm<net.automatalib.automaton.vpa.OneSEVPA<?,I>,I,Boolean>

Direct Known Subclasses:

OPLearnerVPA

public abstract class AbstractVPALearner<I>
extends Object
implements LearningAlgorithm<net.automatalib.automaton.vpa.OneSEVPA<?,I>,I,Boolean>

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	AbstractVPALearner.BuilderDefaults

Nested classes/interfaces inherited from interface de.learnlib.algorithm.LearningAlgorithm

LearningAlgorithm.DFALearner<I>, LearningAlgorithm.MealyLearner<I,O>, LearningAlgorithm.MooreLearner<I,O>, LearningAlgorithm.NFALearner<I>

Field Summary

Fields

Modifier and Type	Field	Description
protected net.automatalib.alphabet.VPAlphabet<I>	alphabet
protected DTree<I>	dtree
protected OneSEVPAHypothesis<I>	hypothesis
protected TransList<I>	openTransitions
protected MembershipOracle<I,Boolean>	oracle

Constructor Summary

Constructors

Constructor	Description
AbstractVPALearner(net.automatalib.alphabet.VPAlphabet<I> alphabet, MembershipOracle<I,Boolean> oracle)

Method Summary

Modifier and Type	Method	Description
protected void	closeTransitions()
protected HypLoc<I>	createLocation(AbstractHypTrans<I> trans)
DTree<I>	getDiscriminationTree()
net.automatalib.automaton.vpa.OneSEVPA<?,I>	getHypothesisModel()	Returns the current hypothesis model.
protected void	initializeLocation(HypLoc<I> loc)
protected static <I> void	link(DTNode<I> leaf, HypLoc<I> loc)
protected HypLoc<I>	makeTree(AbstractHypTrans<I> trans)
boolean	refineHypothesis(DefaultQuery<I,Boolean> ceQuery)	Triggers a refinement of the model by providing a counterexample.
protected abstract boolean	refineHypothesisSingle(DefaultQuery<I,Boolean> ceQuery)
void	startLearning()	Starts the model inference process, creating an initial hypothesis in the provided model object.
protected List<DTNode<I>>	updateDTTargets(List<AbstractHypTrans<I>> trans, boolean hard)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

alphabet

protected final net.automatalib.alphabet.VPAlphabet<I> alphabet

oracle

protected final MembershipOracle<I,Boolean> oracle

dtree

protected final DTree<I> dtree

hypothesis

protected final OneSEVPAHypothesis<I> hypothesis

openTransitions

protected final TransList<I> openTransitions

Constructor Detail

AbstractVPALearner

public AbstractVPALearner(net.automatalib.alphabet.VPAlphabet<I> alphabet,
                          MembershipOracle<I,Boolean> oracle)

Method Detail

startLearning

public void startLearning()

Description copied from interface: LearningAlgorithm

Starts the model inference process, creating an initial hypothesis in the provided model object. Please note that it should be illegal to invoke this method twice.

Specified by:

startLearning in interface LearningAlgorithm<net.automatalib.automaton.vpa.OneSEVPA<?,I>,I,Boolean>

refineHypothesis

public boolean refineHypothesis(DefaultQuery<I,Boolean> ceQuery)

Description copied from interface: LearningAlgorithm

Triggers a refinement of the model by providing a counterexample. A counterexample is a query which exposes different behavior of the real SUL compared to the hypothesis. Please note that invoking this method before an initial invocation of LearningAlgorithm.startLearning() should be illegal.

Specified by:

refineHypothesis in interface LearningAlgorithm<net.automatalib.automaton.vpa.OneSEVPA<?,I>,I,Boolean>

Parameters:

ceQuery - the query which exposes diverging behavior, as posed to the real SUL (i.e. with the SULs output).

Returns:

true if the counterexample triggered a refinement of the hypothesis, false otherwise (i.e., it was no counterexample).

refineHypothesisSingle

protected abstract boolean refineHypothesisSingle(DefaultQuery<I,Boolean> ceQuery)

getHypothesisModel

public net.automatalib.automaton.vpa.OneSEVPA<?,I> getHypothesisModel()

Description copied from interface: LearningAlgorithm

Returns the current hypothesis model.

N.B.: By the contract of this interface, the model returned by this method should not be modified by external code (i.e., M generally should refer to an immutable interface), and its validity is retained only until the next invocation of LearningAlgorithm.refineHypothesis(DefaultQuery). If older hypotheses have to be maintained, a copy of the returned model must be made.

Please note that it should be illegal to invoke this method before an initial invocation of LearningAlgorithm.startLearning().

Specified by:

getHypothesisModel in interface LearningAlgorithm<net.automatalib.automaton.vpa.OneSEVPA<?,I>,I,Boolean>

Returns:

the current hypothesis model.

getDiscriminationTree

public DTree<I> getDiscriminationTree()

link

protected static <I> void link(DTNode<I> leaf,
                               HypLoc<I> loc)

initializeLocation

protected void initializeLocation(HypLoc<I> loc)

closeTransitions

protected void closeTransitions()

updateDTTargets

protected List<DTNode<I>> updateDTTargets(List<AbstractHypTrans<I>> trans,
                                          boolean hard)

makeTree

protected HypLoc<I> makeTree(AbstractHypTrans<I> trans)

createLocation

protected HypLoc<I> createLocation(AbstractHypTrans<I> trans)