Artifacts using LearnLib :: Test Support :: Learning Examples (22)

Support classes for easily writing integration test cases for learning algorithms

A collection of membership oracles

A collection of equivalence oracles

Membership and equivalence oracles using an automaton model as backend

Caches to avoid posing duplicate membership queries

A collection of basic algorithm for approximating equivalence queries

A flexible, optimized version of Dana Angluin's L* algorithm

This artifact provides the implementation of the L* learning algorithm described in the paper "Learning Regular Sets from Queries and Counterexamples" (https://doi.org/10.1016/0890-5401(87)90052-6) by Dana Angluin including variations and optimizations thereof such as the versions based on "On the Learnability of Infinitary Regular Sets" (https://dx.doi.org/10.1006/inco.1995.1070) by Oded Maler and Amir Pnueli or "Inference of finite automata using homing sequences" ...

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 DHC learning algorithm as described in the paper "Automata Learning with on-the-Fly Direct Hypothesis Construction" (https://doi.org/10.1007/978-3-642-34781-8_19) by Maik Merten, Falk Howar, Bernhard Steffen, and Tiziana Margaria.