Group: LearnLib

Module for data structures shared by multiple learning algorithms of LearnLib

This artifact provides the implementations of various learning algorithms based on the "lazy partition refinement" concept as described in the paper "Active Automata Learning as Black-Box Search and Lazy Partition Refinement" (https://doi.org/10.1007/978-3-031-15629-8_17) by Falk Howar and Bernhard Steffen.

This artifact provides the implementation of the L# algorithm as described in the paper "A New Approach for Active Automata Learning Based on Apartness" (https://doi.org/10.1007/978-3-030-99524-9_12) by Frits Vaandrager, Bharat Garhewal, Jurriaan Rot, and Thorsten Wißmann.

Group LearnLib Testsupport

Group LearnLib Distribution

This artifact provides the implementation of the Observation-Pack learning algorithm as described in the PhD thesis "Active learning of interface programs" (http://doi.org/10.17877/DE290R-4817) by Falk Howar.

This artifact 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" (https://doi.org/10.1007/978-3-031-15629-8_17) by Falk Howar and Bernhard Steffen.

This artifact 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" (https://doi.org/10.17877/DE290R-16359) by Malte Isberner.

This artifact 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" (https://doi.org/10.1109/34.211465) by Jose Oncina, Pedro García, and Enrique Vidal.

This artifact 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" (https://doi.org/10.17877/DE290R-16359) by Malte Isberner.

This artifact provides the implementation of the AAAR learning algorithm as described in the paper "Automata Learning with Automated Alphabet Abstraction Refinement" (https://doi.org/10.1007/978-3-642-18275-4_19) by Falk Howar, Bernhard Steffen, and Maik Merten.

This artifact 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 (https://doi.org/10.1007/s10009-021-00634-y) and "From Languages to Behaviors and Back" (https://doi.org/10.1007/978-3-031-15629-8_11) by Markus Frohme and Bernhard Steffen.

Group LearnLib Tooling

Configs and other resources required for building LearnLib

Tools and resources required for building LearnLib

Annotations and processors for the LearnLib build process

A collection of emptiness oracles

A collection of property oracles

A collection of utility methods for learning setups (oracle wrappers, etc.)

A collection of membership oracles