Module de.learnlib.algorithm.adt

Package de.learnlib.algorithm.adt.learner

Class ADTLearner<I,O>

java.lang.Object

de.learnlib.algorithm.adt.learner.ADTLearner<I,O>

Type Parameters:

I - input symbol type

O - output symbol type

All Implemented Interfaces:

PartialTransitionAnalyzer<ADTState<I,O>,I>, LearningAlgorithm<net.automatalib.automaton.transducer.MealyMachine<?,I,?,O>,I,net.automatalib.word.Word<O>>, LearningAlgorithm.MealyLearner<I,O>, Resumable<ADTLearnerState<ADTState<I,O>,I,O>>, net.automatalib.alphabet.SupportsGrowingAlphabet<I>

public class ADTLearner<I,O>
extends Object
implements LearningAlgorithm.MealyLearner<I,O>, PartialTransitionAnalyzer<ADTState<I,O>,I>, net.automatalib.alphabet.SupportsGrowingAlphabet<I>, Resumable<ADTLearnerState<ADTState<I,O>,I,O>>

The main learning algorithm.

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.algorithm.adt.api.PartialTransitionAnalyzer

PartialTransitionAnalyzer.HypothesisModificationException

Field Summary

Fields inherited from interface de.learnlib.algorithm.adt.api.PartialTransitionAnalyzer

HYPOTHESIS_MODIFICATION_EXCEPTION

Constructor Summary

Constructors

Constructor	Description
ADTLearner(net.automatalib.alphabet.Alphabet<I> alphabet, AdaptiveMembershipOracle<I,O> oracle, LeafSplitter leafSplitter, ADTExtender adtExtender, SubtreeReplacer subtreeReplacer)
ADTLearner(net.automatalib.alphabet.Alphabet<I> alphabet, AdaptiveMembershipOracle<I,O> oracle, LeafSplitter leafSplitter, ADTExtender adtExtender, SubtreeReplacer subtreeReplacer, boolean useObservationTree, LocalSuffixFinder<? super I,? super net.automatalib.word.Word<O>> suffixFinder)

Method Summary

Modifier and Type	Method	Description
void	addAlphabetSymbol(I symbol)
void	closeTransition(ADTState<I,O> state, I input)	Determine the successor/output of the transition in question (which is usually achieved by sifting the corresponding long-prefix through the ADT).
ADT<ADTState<I,O>,I,O>	getADT()
net.automatalib.automaton.transducer.MealyMachine<?,I,?,O>	getHypothesisModel()	Returns the current hypothesis model.
boolean	isTransitionDefined(ADTState<I,O> state, I input)	Check whether the transition in question is defined or not.
boolean	refineHypothesis(DefaultQuery<I,net.automatalib.word.Word<O>> ce)	Triggers a refinement of the model by providing a counterexample.
boolean	refineHypothesisInternal(DefaultQuery<I,net.automatalib.word.Word<O>> ceQuery)
void	resume(ADTLearnerState<ADTState<I,O>,I,O> state)	Resume the datastructure from a previously suspended point in time.
void	startLearning()	Starts the model inference process, creating an initial hypothesis in the provided model object.
ADTLearnerState<ADTState<I,O>,I,O>	suspend()	Expose the state object.

Methods inherited from class java.lang.Object

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

Constructor Detail

ADTLearner

public ADTLearner(net.automatalib.alphabet.Alphabet<I> alphabet,
                  AdaptiveMembershipOracle<I,O> oracle,
                  LeafSplitter leafSplitter,
                  ADTExtender adtExtender,
                  SubtreeReplacer subtreeReplacer)

ADTLearner

public ADTLearner(net.automatalib.alphabet.Alphabet<I> alphabet,
                  AdaptiveMembershipOracle<I,O> oracle,
                  LeafSplitter leafSplitter,
                  ADTExtender adtExtender,
                  SubtreeReplacer subtreeReplacer,
                  boolean useObservationTree,
                  LocalSuffixFinder<? super I,? super net.automatalib.word.Word<O>> suffixFinder)

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.transducer.MealyMachine<?,I,?,O>,I,net.automatalib.word.Word<O>>

refineHypothesis

public boolean refineHypothesis(DefaultQuery<I,net.automatalib.word.Word<O>> ce)

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.transducer.MealyMachine<?,I,?,O>,I,net.automatalib.word.Word<O>>

Parameters:

ce - 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).

refineHypothesisInternal

public boolean refineHypothesisInternal(DefaultQuery<I,net.automatalib.word.Word<O>> ceQuery)

getHypothesisModel

public net.automatalib.automaton.transducer.MealyMachine<?,I,?,O> 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.transducer.MealyMachine<?,I,?,O>,I,net.automatalib.word.Word<O>>

Returns:

the current hypothesis model.

closeTransition

public void closeTransition(ADTState<I,O> state,
                            I input)

Description copied from interface: PartialTransitionAnalyzer

Determine the successor/output of the transition in question (which is usually achieved by sifting the corresponding long-prefix through the ADT).

Specified by:

closeTransition in interface PartialTransitionAnalyzer<I,O>

Parameters:

state - the (source) state of the transition in question

input - the input symbol of the transition in question

isTransitionDefined

public boolean isTransitionDefined(ADTState<I,O> state,
                                   I input)

Description copied from interface: PartialTransitionAnalyzer

Check whether the transition in question is defined or not.

Specified by:

isTransitionDefined in interface PartialTransitionAnalyzer<I,O>

Parameters:

state - the (source) state of the transition in question

input - the input symbol of the transition in question

Returns:

true if the transition (and thus the successor/output) is defined, false otherwise

addAlphabetSymbol

public void addAlphabetSymbol(I symbol)

Specified by:

addAlphabetSymbol in interface net.automatalib.alphabet.SupportsGrowingAlphabet<I>

suspend

public ADTLearnerState<ADTState<I,O>,I,O> suspend()

Description copied from interface: Resumable

Expose the state object.

Specified by:

suspend in interface Resumable<I>

Returns:

The state.

resume

public void resume(ADTLearnerState<ADTState<I,O>,I,O> state)

Description copied from interface: Resumable

Resume the datastructure from a previously suspended point in time.

Specified by:

resume in interface Resumable<I>

Parameters:

state - The learner state.

getADT

public ADT<ADTState<I,O>,I,O> getADT()