Abstract
This paper presents libalf, a comprehensive, open-source library for learning formal languages. libalf covers various well-known learning techniques for finite automata (e.g. Angluin's L*, Biermann, RPNI etc.) as well as novel learning algorithms (such as for NFA and visibly one-counter automata). libalf is flexible and allows facilely interchanging learning algorithms and combining domain-specific features in a plug-and-play fashion. Its modular design and C++ implementation make it a suitable platform for adding and engineering further learning algorithms for new target models (e.g., Büchi automata). © 2010 Springer-Verlag.
Cite
CITATION STYLE
Bollig, B., Katoen, J. P., Kern, C., Leucker, M., Neider, D., & Piegdon, D. R. (2010). libalf: The automata learning framework. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6174 LNCS, pp. 360–364). https://doi.org/10.1007/978-3-642-14295-6_32
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