Verifying Liveness by Augmented Abstraction

  • Yonit Kesten
  • Amir Pnueli
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1683)


The paper deals with the proof method of verification by augmented finitary abstraction (VAA), which presents an effective approach to the verification of the temporal properties of (potentially infinitestate) reactive systems. The method consists of a two-step process by which, in a first step, the system and its temporal specification are combined an then abstracted into a finite-state Büchi automaton. The second step uses model checking to establish emptiness of the abstracted automaton.

The (VAA) method can be considered as a viable alternative to verification by temporal deduction which, up to now, has been the main method shown to be complete for the verification of infinite-state systems.

The paper presents a general recipe for the abstraction of Büchi automata which is shown to be sound, where soundness means that emptiness of the abstract automaton implies emptiness of the concrete (infinitestate) automaton. To make the method applicable for the verification of liveness properties, pure abstraction is sometimes no longer adequate.We show that by augmenting the system by an appropriate (and standardly constructible) progress monitor, we obtain an augmented system, whose computations are essentially the same as the original system, and which may now be abstracted while preserving the desired liveness properties. We then proceed to show that the (VAA) method is sound and complete for proving all properties expressible by temporal logic (including both safety and liveness). Completeness establishes that whenever an infinite-state Büchi automaton has no computations, there exists a finitary abstraction which abstracts the automaton, augmented by an appropriate progress monitor, into a finite-state Büchi automaton with no computations


Model Check Temporal Property Ranking Function Linear Temporal Logic Augmented System 
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 1999

Authors and Affiliations

  • Yonit Kesten
  • Amir Pnueli

There are no affiliations available

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