A small Java Annotation Processor library which for automatically generating Builder classes from constructors or static methods.

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 ...

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.

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, ...

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 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" ...

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" ...

This artifact provides the integration of the model checker "LTSmin" (https://ltsmin.utwente.nl/) as described in the paper "Sound Black-Box Checking in the LearnLib" (https://doi.org/10.1007/s11334-019-00342-6) by Jeroen Meijer and ...

This artifact provides the implementation of the ADT learning algorithm as described in the Master thesis "Active Automata Learning with Adaptive Distinguishing Sequences" (http://arxiv.org/abs/1902.01139) by Markus Frohme.

This artifact provides the implementation of the NL* learning algorithm as described in the paper "Angluin-Style Learning of NFA" (http://ijcai.org/Proceedings/09/Papers/170.pdf) by Benedikt Bollig, Peter Habermehl, Carsten Kern, and ...