LearnLib: a library for automata learning and experimentation

  • Authors:
  • Harald Raffelt;Bernhard Steffen;Therese Berg

  • Affiliations:
  • University of Dortmund, Dortmund, Germany;University of Dortmund, Dortmund, Germany;Uppsala University, Uppsala, Sweden

  • Venue:
  • Proceedings of the 10th international workshop on Formal methods for industrial critical systems
  • Year:
  • 2005

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Abstract

In this paper we present the LearnLib, a library for automata learning and experimentation. Its modular structure allows users to configure their tailored learning scenarios, which exploit specific properties of the envisioned applications. As has been shown earlier, exploiting application-specific structural features enables optimizations that may lead to performance gains of several orders of magnitude, a necessary precondition to make automata learning applicable to realistic scenarios.