Abstraction-Guided model checking using symbolic IDA* and heuristic synthesis

  • Authors:

  • Kairong Qian;Albert Nymeyer;Steven Susanto

  • Affiliations:

  • School of Computer Science & Engineering, The University of New South Wales, Sydney, Australia;School of Computer Science & Engineering, The University of New South Wales, Sydney, Australia;School of Computer Science & Engineering, The University of New South Wales, Sydney, Australia

  • Venue:
  • FORTE'05 Proceedings of the 25th IFIP WG 6.1 international conference on Formal Techniques for Networked and Distributed Systems
  • Year:
  • 2005

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Abstract

A heuristic-based symbolic model checking algorithm, BDD-IDA*. that efficiently falsifies invariant properties of a system is presented. As in bounded model checking, the algorithm uses an iterative deepening search strategy. However, in our case, the search strategy is guided by a heuristic that is computed from an abstract model, which is derived from the concrete model by a synthesis technique. Synthesis involves eliminating so-called weak variables from the concrete specification, where the weak variables are identified by a data-dependency analysis. Unique to this work is the use of the depth-first IDA* search algorithm in a BDD setting, and the automatic synthesis of the heuristic. The performance of the approach on a large number of small examples is compared with standard BDD-based approaches. Experiments on a variety of real-world models from different domains are also conducted. The approach reveals a consistent improvement on all models, and in some cases a speed-up of 2 orders of magnitude is obtained.