LearnLib 0.17.0 API

Packages

Package	Description
de.learnlib
de.learnlib.acex	This package provides interfaces and classes for the abstract counterexample analysis framework described in the paper An Abstract Framework for Counterexample Analysis in Active Automata Learning by Malte Isberner and Bernhard Steffen.
de.learnlib.algorithm	This package (including sub-packages) contains the basic interfaces and classes of learning algorithms of LearnLib.
de.learnlib.algorithm.aaar	This package (and sub-packages) provides the implementation of the AAAR learning algorithm as described in the paper Automata Learning with Automated Alphabet Abstraction Refinement by Falk Howar, Bernhard Steffen, and Maik Merten.
de.learnlib.algorithm.aaar.abstraction
de.learnlib.algorithm.aaar.explicit
de.learnlib.algorithm.aaar.generic
de.learnlib.algorithm.adt	This package (and sub-packages) provides the implementation of the ADT learning algorithm as described in the Master thesis Active Automata Learning with Adaptive Distinguishing Sequences by Markus Frohme.
de.learnlib.algorithm.adt.ads
de.learnlib.algorithm.adt.adt
de.learnlib.algorithm.adt.api
de.learnlib.algorithm.adt.automaton
de.learnlib.algorithm.adt.config
de.learnlib.algorithm.adt.config.model
de.learnlib.algorithm.adt.config.model.calculator
de.learnlib.algorithm.adt.config.model.extender
de.learnlib.algorithm.adt.config.model.replacer
de.learnlib.algorithm.adt.learner
de.learnlib.algorithm.adt.model
de.learnlib.algorithm.adt.util
de.learnlib.algorithm.dhc	This package (and sub-packages) provides the implementation of the DHC learning algorithm as described in the paper Automata Learning with on-the-Fly Direct Hypothesis Construction by Maik Merten, Falk Howar, Bernhard Steffen, and Tiziana Margaria.
de.learnlib.algorithm.dhc.mealy
de.learnlib.algorithm.kv	This package (and sub-packages) provides the implementation of the learning algorithm described in the book "An Introduction to Computational Learning Theory" by Michael Kearns and Umesh Vazirani.
de.learnlib.algorithm.kv.dfa
de.learnlib.algorithm.kv.mealy
de.learnlib.algorithm.lstar	This package (and sub-packages) provides the implementation of the L* learning algorithm described in the paper Learning Regular Sets from Queries and Counterexamples by Dana Angluin as well as multiple variations thereof.
de.learnlib.algorithm.lstar.ce
de.learnlib.algorithm.lstar.closing
de.learnlib.algorithm.lstar.dfa
de.learnlib.algorithm.lstar.mealy
de.learnlib.algorithm.lstar.moore
de.learnlib.algorithm.malerpnueli	This package (and sub-packages) provides the implementation of the L* variation based on the paper On the Learnability of Infinitary Regular Sets by Oded Maler and Amir Pnueli.
de.learnlib.algorithm.nlstar	This package (and sub-packages) provides the implementation of the NL* learning algorithm as described in the paper Angluin-Style Learning of NFA by Benedikt Bollig, Peter Habermehl, Carsten Kern, and Martin Leucker.
de.learnlib.algorithm.observationpack	This package (and sub-packages) provides the implementation of the Observation-Pack learning algorithm as described in the PhD thesis Active learning of interface programs by Falk Howar.
de.learnlib.algorithm.observationpack.dfa
de.learnlib.algorithm.observationpack.hypothesis
de.learnlib.algorithm.observationpack.mealy
de.learnlib.algorithm.observationpack.moore
de.learnlib.algorithm.observationpack.vpa	This package (and sub-packages) provides the implementation of the VPA adaption of the Observation-Pack learning algorithm as discussed in the PhD thesis Foundations of Active Automata Learning: An Algorithmic Perspective by Malte Isberner.
de.learnlib.algorithm.observationpack.vpa.hypothesis
de.learnlib.algorithm.oml	This package (and sub-packages) provides the implementations of various learning algorithms based on the "optimal MAT learning" concept as described in the paper Active Automata Learning as Black-Box Search and Lazy Partition Refinement by Falk Howar and Bernhard Steffen.
de.learnlib.algorithm.oml.lstar
de.learnlib.algorithm.oml.ttt
de.learnlib.algorithm.oml.ttt.dfa
de.learnlib.algorithm.oml.ttt.dt
de.learnlib.algorithm.oml.ttt.mealy
de.learnlib.algorithm.oml.ttt.pt
de.learnlib.algorithm.oml.ttt.st
de.learnlib.algorithm.ostia	This package (and sub-packages) provides the implementation of the "onward subsequential transducer inference algorithm" (OSTIA) learning algorithm as presented in the paper Learning Subsequential Transducers for Pattern Recognition Interpretation Tasks by Jose Oncina, Pedro García, and Enrique Vidal.
de.learnlib.algorithm.procedural	This package (and sub-packages) provides the implementations of various learning algorithms for systems of procedural automata such as the ones described in the papers Compositional learning of mutually recursive procedural systems and From Languages to Behaviors and Back by Markus Frohme and Bernhard Steffen.
de.learnlib.algorithm.procedural.adapter.dfa
de.learnlib.algorithm.procedural.adapter.mealy
de.learnlib.algorithm.procedural.sba
de.learnlib.algorithm.procedural.sba.manager
de.learnlib.algorithm.procedural.spa
de.learnlib.algorithm.procedural.spa.manager
de.learnlib.algorithm.procedural.spmm
de.learnlib.algorithm.procedural.spmm.manager
de.learnlib.algorithm.rivestschapire	This package (and sub-packages) provides the implementation of the L* variation based on the paper Inference of finite automata using homing sequences by Ronald L. Rivest and Robert E. Schapire.
de.learnlib.algorithm.rpni	This package (and sub-packages) provides the implementation of (a blue-fringe version of) the "regular positive negative inference" (RPNI) learning algorithm as presented in the paper Inferring regular languages in polynomial update time by Jose Oncina and Pedro García.
de.learnlib.algorithm.ttt	This package (and sub-packages) provides the implementation of the TTT algorithm as described in the paper The TTT Algorithm: A Redundancy-Free Approach to Active Automata Learning by Malte Isberner, Falk Howar, and Bernhard Steffen.
de.learnlib.algorithm.ttt.base
de.learnlib.algorithm.ttt.dfa
de.learnlib.algorithm.ttt.mealy
de.learnlib.algorithm.ttt.moore
de.learnlib.algorithm.ttt.vpa	This package (and sub-packages) provides the implementation of the VPA adaption of the TTT learning algorithm as presented in the PhD thesis Foundations of Active Automata Learning: An Algorithmic Perspective by Malte Isberner.
de.learnlib.buildtool	This package (including sub-packages) contains utility code for the build process of LearnLib.
de.learnlib.buildtool.refinement.annotation
de.learnlib.buildtool.refinement.processor
de.learnlib.counterexample	This package contains a collection of standard algorithms for handling counterexamples in automata learning.
de.learnlib.datastructure.discriminationtree
de.learnlib.datastructure.discriminationtree.iterators
de.learnlib.datastructure.discriminationtree.model
de.learnlib.datastructure.list
de.learnlib.datastructure.observationtable
de.learnlib.datastructure.observationtable.reader
de.learnlib.datastructure.observationtable.writer
de.learnlib.datastructure.pta
de.learnlib.datastructure.pta.config
de.learnlib.datastructure.pta.wrapper
de.learnlib.driver
de.learnlib.driver.reflect
de.learnlib.driver.simulator
de.learnlib.example	This package (including sub-packages) contains example models of various types used in integration-tests.
de.learnlib.example.dfa
de.learnlib.example.mealy
de.learnlib.example.moore
de.learnlib.example.sba
de.learnlib.example.spa
de.learnlib.example.spmm
de.learnlib.example.sst
de.learnlib.example.vpa
de.learnlib.exception
de.learnlib.filter.cache
de.learnlib.filter.cache.dfa
de.learnlib.filter.cache.mealy
de.learnlib.filter.cache.moore
de.learnlib.filter.cache.sul
de.learnlib.filter.reuse
de.learnlib.filter.reuse.tree
de.learnlib.filter.statistic
de.learnlib.filter.statistic.learner
de.learnlib.filter.statistic.oracle
de.learnlib.filter.statistic.sul
de.learnlib.logging
de.learnlib.mapper
de.learnlib.oracle	This package (including sub-packages) contains the basic interfaces and classes for describing and implementing various types of oracles used throughout LearnLib.
de.learnlib.oracle.emptiness
de.learnlib.oracle.equivalence
de.learnlib.oracle.equivalence.mealy
de.learnlib.oracle.equivalence.sba
de.learnlib.oracle.equivalence.spa
de.learnlib.oracle.equivalence.spmm
de.learnlib.oracle.equivalence.vpa
de.learnlib.oracle.membership
de.learnlib.oracle.parallelism
de.learnlib.oracle.property
de.learnlib.query
de.learnlib.setting
de.learnlib.setting.sources
de.learnlib.statistic
de.learnlib.sul	This package (and related packages) contains interfaces and classes for formalizing access to systems under learning (SULs).
de.learnlib.testsupport	This package (including sub-packages) contains utility code for formalizing test-cases.
de.learnlib.testsupport.it.learner
de.learnlib.util	This package (and sub-packages) provide general utilities used throughout LearnLib.
de.learnlib.util.mealy
de.learnlib.util.moore
de.learnlib.util.nfa
de.learnlib.util.statistic