Infrastructure and core functionalities of LearnLib

Support classes for easily writing integration test cases for learning algorithms

A collection of algorithms for handling counterexamples in automata learning

Caches to avoid posing duplicate membership queries

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 ...

This artifact provides the implementation of the learning algorithm described in the book "An Introduction to Computational Learning Theory" by Michael Kearns and Umesh Vazirani.

Support for posing membership queries in parallel

This artifact provides the implementation of the TTT algorithm as described in the paper "The TTT Algorithm: A Redundancy-Free Approach to Active Automata Learning" (https://doi.org/10.1007/978-3-319-11164-3_26) by Malte Isberner, ...

Basic support for test driver creation

Translation utilities for mapping abstract hypothesis symbols to concrete SUL symbols

Reuse Tree for (intelligently) caching membership queries as described in the paper "Reusing System States by Active Learning Algorithms" (https://doi.org/10.1007/978-3-642-28033-7_6) by Oliver Bauer, Johannes Neubauer, Bernhard ...