Package de.learnlib.algorithm.oml.ttt

Class AbstractOptimalTTT<M,I,D>

java.lang.Object

de.learnlib.algorithm.oml.ttt.AbstractOptimalTTT<M,I,D>

All Implemented Interfaces:

LearningAlgorithm<M,I,D>, SupportsGrowingAlphabet<I>, InputAlphabetHolder<I>

Direct Known Subclasses:

OptimalTTTDFA, OptimalTTTMealy

public abstract class AbstractOptimalTTT<M,I,D>
extends Object
implements LearningAlgorithm<M,I,D>, SupportsGrowingAlphabet<I>, InputAlphabetHolder<I>

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>

Field Summary

Fields

Modifier and Type	Field	Description
protected PrefixTree<I,D>	ptree
protected SuffixTrie<I>	strie

Constructor Summary

Constructors

Modifier	Constructor	Description
protected	AbstractOptimalTTT(Alphabet<I> alphabet, MembershipOracle<I,D> ceqs)

Method Summary

Modifier and Type	Method	Description
void	addAlphabetSymbol(I symbol)
protected abstract AbstractDecisionTree<I,D>	dtree()
Alphabet<I>	getInputAlphabet()
protected abstract DTLeaf<I,D>	getState(Word<I> prefix)
protected abstract D	hypOutput(Word<I> word, int length)
protected abstract boolean	isCanonical()
protected abstract int	maxSearchIndex(int ceLength)
boolean	refineHypothesis(DefaultQuery<I,D> counterexample)	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.
protected abstract D	suffix(D output, int length)

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.learnlib.algorithm.LearningAlgorithm

getHypothesisModel

Field Detail

strie

protected final SuffixTrie<I> strie

ptree

protected final PrefixTree<I,D> ptree

Constructor Detail

AbstractOptimalTTT

protected AbstractOptimalTTT(Alphabet<I> alphabet,
                             MembershipOracle<I,D> ceqs)

Method Detail

maxSearchIndex

protected abstract int maxSearchIndex(int ceLength)

hypOutput

protected abstract D hypOutput(Word<I> word,
                               int length)

getState

protected abstract DTLeaf<I,D> getState(Word<I> prefix)

dtree

protected abstract AbstractDecisionTree<I,D> dtree()

suffix

protected abstract D suffix(D output,
                            int length)

isCanonical

protected abstract boolean isCanonical()

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> counterexample)

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:

counterexample - 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).

addAlphabetSymbol

public void addAlphabetSymbol(I symbol)

Specified by:

addAlphabetSymbol in interface SupportsGrowingAlphabet<M>

getInputAlphabet

public Alphabet<I> getInputAlphabet()

Specified by:

getInputAlphabet in interface InputAlphabetHolder<M>