2010 | OriginalPaper | Buchkapitel
libalf: The Automata Learning Framework
verfasst von : Benedikt Bollig, Joost-Pieter Katoen, Carsten Kern, Martin Leucker, Daniel Neider, David R. Piegdon
Erschienen in: Computer Aided Verification
Verlag: Springer Berlin Heidelberg
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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).