libalf: The Automata Learning Framework

  • Benedikt Bollig
  • Joost-Pieter Katoen
  • Carsten Kern
  • Martin Leucker
  • Daniel Neider
  • David R. Piegdon
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6174)

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).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Benedikt Bollig
    • 1
  • Joost-Pieter Katoen
    • 2
  • Carsten Kern
    • 2
  • Martin Leucker
    • 3
  • Daniel Neider
    • 2
  • David R. Piegdon
    • 2
  1. 1.LSV, ENS Cachan, CNRS 
  2. 2.RWTH Aachen University 
  3. 3.TU München 

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