Uses of Class
de.learnlib.algorithms.discriminationtree.hypothesis.HState

Packages that use HState

Package	Description
de.learnlib.algorithms.discriminationtree
de.learnlib.algorithms.discriminationtree.dfa
de.learnlib.algorithms.discriminationtree.hypothesis
de.learnlib.algorithms.discriminationtree.mealy

Uses of HState in de.learnlib.algorithms.discriminationtree

Fields in de.learnlib.algorithms.discriminationtree with type parameters of type HState

Modifier and Type	Field and Description
protected DiscriminationTree<I,O,HState<I,O,SP,TP>>	AbstractDTLearner.dtree

Methods in de.learnlib.algorithms.discriminationtree that return HState

Modifier and Type	Method and Description
protected HState<I,O,SP,TP>	AbstractDTLearner.createState(HTransition<I,O,SP,TP> trans)

Methods in de.learnlib.algorithms.discriminationtree that return types with arguments of type HState

Modifier and Type	Method and Description
DiscriminationTree<I,O,HState<I,O,SP,TP>>	AbstractDTLearner.getDiscriminationTree()

Methods in de.learnlib.algorithms.discriminationtree with parameters of type HState

Modifier and Type	Method and Description
protected void	AbstractDTLearner.initializeState(HState<I,O,SP,TP> newState)
protected abstract Query<I,O>	AbstractDTLearner.spQuery(HState<I,O,SP,TP> state)

Constructor parameters in de.learnlib.algorithms.discriminationtree with type arguments of type HState

Constructor and Description
AbstractDTLearner(net.automatalib.words.Alphabet<I> alphabet, MembershipOracle<I,O> oracle, LocalSuffixFinder<? super I,? super O> suffixFinder, boolean repeatedCounterexampleEvaluation, DiscriminationTree<I,O,HState<I,O,SP,TP>> dtree)

Uses of HState in de.learnlib.algorithms.discriminationtree.dfa

Methods in de.learnlib.algorithms.discriminationtree.dfa with parameters of type HState

Modifier and Type	Method and Description
protected Query<I,Boolean>	DTLearnerDFA.spQuery(HState<I,Boolean,Boolean,Void> state)

Uses of HState in de.learnlib.algorithms.discriminationtree.hypothesis

Methods in de.learnlib.algorithms.discriminationtree.hypothesis that return HState

Modifier and Type	Method and Description
HState<I,O,SP,TP>	DTLearnerHypothesis.createState(HTransition<I,O,SP,TP> treeIncoming)
HState<I,O,SP,TP>	HTransition.currentTarget()
HState<I,O,SP,TP>	DTLearnerHypothesis.getInitialState()
HState<I,O,SP,TP>	DTLearnerHypothesis.GraphView.getNode(int id)
HState<I,O,SP,TP>	HTransition.getSource()
HState<I,O,SP,TP>	DTLearnerHypothesis.getState(int id)
HState<I,O,SP,TP>	DTLearnerHypothesis.getSuccessor(HTransition<I,O,SP,TP> trans)
HState<I,O,SP,TP>	DTLearnerHypothesis.GraphView.getTarget(HTransition<I,O,SP,TP> edge)
HState<I,O,SP,TP>	HTransition.getTreeTarget()
HState<I,O,SP,TP>	HTransition.nonTreeTarget()

Methods in de.learnlib.algorithms.discriminationtree.hypothesis that return types with arguments of type HState

Modifier and Type	Method and Description
DTNode<I,O,HState<I,O,SP,TP>>	HTransition.getDT()
DTNode<I,O,HState<I,O,SP,TP>>	HState.getDTLeaf()
net.automatalib.graphs.dot.GraphDOTHelper<HState<I,O,SP,TP>,HTransition<I,O,SP,TP>>	DTLearnerHypothesis.GraphView.getGraphDOTHelper()
Collection<HState<I,O,SP,TP>>	DTLearnerHypothesis.GraphView.getNodes()
Collection<HState<I,O,SP,TP>>	DTLearnerHypothesis.getStates()
net.automatalib.graphs.concepts.NodeIDs<HState<I,O,SP,TP>>	DTLearnerHypothesis.GraphView.nodeIDs()
net.automatalib.automata.concepts.StateIDs<HState<I,O,SP,TP>>	DTLearnerHypothesis.stateIDs()

Methods in de.learnlib.algorithms.discriminationtree.hypothesis with parameters of type HState

Modifier and Type	Method and Description
int	DTLearnerHypothesis.GraphView.getNodeId(HState<I,O,SP,TP> node)
Collection<HTransition<I,O,SP,TP>>	DTLearnerHypothesis.GraphView.getOutgoingEdges(HState<I,O,SP,TP> node)
int	DTLearnerHypothesis.getStateId(HState<I,O,SP,TP> state)
SP	DTLearnerHypothesis.getStateProperty(HState<I,O,SP,TP> state)
HTransition<I,O,SP,TP>	DTLearnerHypothesis.getTransition(HState<I,O,SP,TP> state, I symbol)
void	HTransition.makeTree(HState<I,O,SP,TP> treeTgt)

Method parameters in de.learnlib.algorithms.discriminationtree.hypothesis with type arguments of type HState

Modifier and Type	Method and Description
void	HTransition.setDT(DTNode<I,O,HState<I,O,SP,TP>> dtNode)
void	HState.setDTLeaf(DTNode<I,O,HState<I,O,SP,TP>> dtLeaf)

Constructors in de.learnlib.algorithms.discriminationtree.hypothesis with parameters of type HState

Constructor and Description
HTransition(HState<I,O,SP,TP> source, I symbol, DTNode<I,O,HState<I,O,SP,TP>> dtTgt)

Constructor parameters in de.learnlib.algorithms.discriminationtree.hypothesis with type arguments of type HState

Constructor and Description
HTransition(HState<I,O,SP,TP> source, I symbol, DTNode<I,O,HState<I,O,SP,TP>> dtTgt)

Uses of HState in de.learnlib.algorithms.discriminationtree.mealy

Methods in de.learnlib.algorithms.discriminationtree.mealy with parameters of type HState

Modifier and Type	Method and Description
protected Query<I,net.automatalib.words.Word<O>>	DTLearnerMealy.spQuery(HState<I,net.automatalib.words.Word<O>,Void,O> state)