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Inferring Network Invariants Automatically

  • Olga Grinchtein
  • Martin Leucker
  • Nir Piterman
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4130)

Abstract

Verification by network invariants is a heuristic to solve uniform verification of parameterized systems. Given a system P, a network invariant for P is a system that abstracts the composition of every number of copies of P running in parallel. If there is such a network invariant, by reasoning about it, uniform verification with respect to the family P[1] ∥ ⋯ ∥ P[n] can be carried out. In this paper, we propose a procedure that searches systematically for a network invariant satisfying a given safety property. The search is based on algorithms for learning finite automata due to Angluin and Biermann. We optimize the search by combining both algorithms for improving successive possible invariants. We also show how to reduce the learning problem to SAT, allowing efficient SAT solvers to be used, which turns out to yield a very competitive learning algorithm. The overall search procedure finds a minimal such invariant, if it exists.

Keywords

Constraint Satisfaction Problem Regular Language Conjunctive Normal Form Safety Property Network Invariant 
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 2006

Authors and Affiliations

  • Olga Grinchtein
    • 1
  • Martin Leucker
    • 2
  • Nir Piterman
    • 3
  1. 1.Department of Computer SystemsUppsala UniversitySweden
  2. 2.IT DepartmentTU MunichGermany
  3. 3.EPFLLausanneSwitzerland

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