de.learnlib.algorithms.discriminationtree.vpda

Class AbstractVPDALearner<I>

java.lang.Object

de.learnlib.algorithms.discriminationtree.vpda.AbstractVPDALearner<I>

Type Parameters:

I - input alphabet type

All Implemented Interfaces:

LearningAlgorithm<net.automatalib.automata.vpda.OneSEVPA<?,I>,I,Boolean>

Direct Known Subclasses:

DTLearnerVPDA

public abstract class AbstractVPDALearner<I>
extends Object
implements LearningAlgorithm<net.automatalib.automata.vpda.OneSEVPA<?,I>,I,Boolean>

Author:

Malte Isberner

Nested Class Summary

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

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

Field Summary

Fields

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

Constructor Summary

Constructors

Constructor and Description
AbstractVPDALearner(net.automatalib.words.VPDAlphabet<I> alphabet, MembershipOracle<I,Boolean> oracle)

Method Summary

Modifier and Type	Method and Description
protected void	closeTransitions()
protected HypLoc<I>	createLocation(AbstractHypTrans<I> trans)
protected HypLoc<I>	createLocation(net.automatalib.words.Word<I> as)
net.automatalib.automata.vpda.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)
protected Boolean	query(AccessSequenceProvider<I> asp, ContextPair<I> context)
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 DTNode<I>	updateDTTarget(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.words.VPDAlphabet<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

AbstractVPDALearner

public AbstractVPDALearner(net.automatalib.words.VPDAlphabet<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.automata.vpda.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.automata.vpda.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.automata.vpda.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 may not be modified (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.automata.vpda.OneSEVPA<?,I>,I,Boolean>

Returns:

the current hypothesis model.

link

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

initializeLocation

protected void initializeLocation(HypLoc<I> loc)

closeTransitions

protected void closeTransitions()

updateDTTarget

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

makeTree

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

createLocation

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

createLocation

protected HypLoc<I> createLocation(net.automatalib.words.Word<I> as)

query

protected Boolean query(AccessSequenceProvider<I> asp,
                        ContextPair<I> context)