Package de.learnlib.algorithm.nlstar

Class NLStarLearner<I>

java.lang.Object

de.learnlib.algorithm.nlstar.NLStarLearner<I>

Type Parameters:

I - input symbol type

All Implemented Interfaces:

LearningAlgorithm<NFA<?,I>,I,Boolean>, LearningAlgorithm.NFALearner<I>

public class NLStarLearner<I>
extends Object
implements LearningAlgorithm.NFALearner<I>

The NL* learner.

Nested Class Summary

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

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

Constructor Summary

Constructors

Constructor	Description
NLStarLearner(Alphabet<I> alphabet, MembershipOracle<I,Boolean> oracle)	Constructor.

Method Summary

Modifier and Type	Method	Description
LearningAlgorithm.DFALearner<I>	asDFALearner()	Retrieves a view of this learner as a DFA learner.
CompactDFA<I>	getDeterminizedHypothesis()	Retrieves a deterministic version of the hypothesis.
CompactNFA<I>	getHypothesisModel()	Returns the current hypothesis model.
ObservationTable<I>	getObservationTable()
boolean	refineHypothesis(DefaultQuery<I,Boolean> ceQuery)	Triggers a refinement of the model by providing a counterexample.
void	startLearning()	Starts the model inference process, creating an initial hypothesis in the provided model object.

Methods inherited from class java.lang.Object

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

Constructor Detail

NLStarLearner

public NLStarLearner(Alphabet<I> alphabet,
                     MembershipOracle<I,Boolean> oracle)

Constructor.

Parameters:

alphabet - the input alphabet

oracle - the membership 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<NFA<?,I>,I,Boolean>

asDFALearner

public LearningAlgorithm.DFALearner<I> asDFALearner()

Retrieves a view of this learner as a DFA learner. The DFA is obtained by determinizing and minimizing the NFA hypothesis.

Returns:

a DFA learner view of this learner

See Also:

getDeterminizedHypothesis()

getDeterminizedHypothesis

public CompactDFA<I> getDeterminizedHypothesis()

Retrieves a deterministic version of the hypothesis. The DFA is obtained through NFAs.determinize(net.automatalib.automaton.fsa.NFA).

Returns:

a deterministic version of the hypothesis

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<NFA<?,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).

getHypothesisModel

public CompactNFA<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<NFA<?,I>,I,Boolean>

Returns:

the current hypothesis model.

getObservationTable

public ObservationTable<I> getObservationTable()