Package de.learnlib.filter.statistic.learner

Class RefinementCounterLearner<M,I,D>

java.lang.Object

de.learnlib.filter.statistic.learner.RefinementCounterLearner<M,I,D>

Type Parameters:

M - the automaton type.

I - the input type.

D - the output type.

All Implemented Interfaces:

LearningAlgorithm<M,I,D>, StatisticCollector, StatisticLearner<M,I,D>

Direct Known Subclasses:

DFARefinementCounterLearner, MealyRefinementCounterLearner, MooreRefinementCounterLearner

public class RefinementCounterLearner<M,I,D>
extends Object
implements StatisticLearner<M,I,D>

Counts the number of hypothesis refinements.

The value of the Counter returned by getStatisticalData() returns the same value as Experiment.getRounds().

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>

Nested classes/interfaces inherited from interface de.learnlib.statistic.StatisticLearner

StatisticLearner.DFAStatisticLearner<I>, StatisticLearner.MealyStatisticLearner<I,O>, StatisticLearner.MooreStatisticLearner<I,O>

Constructor Summary

Constructors

Constructor	Description
RefinementCounterLearner(LearningAlgorithm<M,I,D> learningAlgorithm)

Method Summary

Modifier and Type	Method	Description
M	getHypothesisModel()	Returns the current hypothesis model.
Counter	getStatisticalData()	Returns this statistical data gathered by this collector.
boolean	refineHypothesis(DefaultQuery<I,D> 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

RefinementCounterLearner

public RefinementCounterLearner(LearningAlgorithm<M,I,D> learningAlgorithm)

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<M,I,D>

refineHypothesis

public boolean refineHypothesis(DefaultQuery<I,D> 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<M,I,D>

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 M 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<M,I,D>

Returns:

the current hypothesis model.

getStatisticalData

public Counter getStatisticalData()

Description copied from interface: StatisticCollector

Returns this statistical data gathered by this collector.

Specified by:

getStatisticalData in interface StatisticCollector

Returns:

the statistical data gathered by this collector