The libalf library is a comprehensive, open-source library for learning finite-state automata covering various well-known learning techniques (such as Angluin's L*, Biermann's learning approach, and RPNI), as well as novel learning algorithms (e.g. for NFA and visibly one-counter automata).

libalf is highly flexible and allows for facilely interchanging learning algorithms and combining domain-specific features in a plug-and-play fashion. Its modular design and its implementation in C++ make it the ideal platform for adding and engineering further, efficient learning algorithms for new target models (e.g., Büchi automata, timed automata, or probabilistic automata).

Currently, the following learning algorithms are supported:

Glossary