Extending Automated Compositional Verification to the Full Class of Omega-Regular Languages

  • Azadeh Farzan
  • Yu-Fang Chen
  • Edmund M. Clarke
  • Yih-Kuen Tsay
  • Bow-Yaw Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4963)


Recent studies have suggested the applicability of learning to automated compositional verification. However, current learning algorithms fall short when it comes to learning liveness properties. We extend the automaton synthesis paradigm for the infinitary languages by presenting an algorithm to learn an arbitrary regular set of infinite sequences (an ω-regular language) over an alphabet Σ. Our main result is an algorithm to learn a nondeterministic Büchi automaton that recognizes an unknown ω-regular language. This is done by learning a unique projection of it on Σ * using the framework suggested by Angluin for learning regular subsets of Σ *.


Target Language Equivalence Check Regular Language Liveness Property Membership Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Azadeh Farzan
    • 1
  • Yu-Fang Chen
    • 2
  • Edmund M. Clarke
    • 1
  • Yih-Kuen Tsay
    • 2
  • Bow-Yaw Wang
    • 3
  1. 1.Carnegie Mellon University 
  2. 2.National Taiwan University 
  3. 3.Academia Sinica 

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