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Invariant Checking of NRA Transition Systems via Incremental Reduction to LRA with EUF

  • Alessandro Cimatti
  • Alberto Griggio
  • Ahmed IrfanEmail author
  • Marco Roveri
  • Roberto Sebastiani
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10205)

Abstract

Model checking invariant properties of designs, represented as transition systems, with non-linear real arithmetic (NRA), is an important though very hard problem. On the one hand NRA is a hard-to-solve theory; on the other hand most of the powerful model checking techniques lack support for NRA. In this paper, we present a counterexample-guided abstraction refinement (CEGAR) approach that leverages linearization techniques from differential calculus to enable the use of mature and efficient model checking algorithms for transition systems on linear real arithmetic (LRA) with uninterpreted functions (EUF). The results of an empirical evaluation confirm the validity and potential of this approach.

Keywords

Linear Real Arithmetic (LRA) Invariant Checking Uninterpreted Functions Abstraction Refinement Safety Benchmark 
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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Notes

Acknowledgement

We greatly thank the iSAT3 team for providing the latest iSAT3 executable and iSAT3-CFG benchmarks. We also thank James Davenport for the fruitful discussions on CAD techniques and finding solutions in NRA.

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Alessandro Cimatti
    • 1
  • Alberto Griggio
    • 1
  • Ahmed Irfan
    • 1
    • 2
    Email author
  • Marco Roveri
    • 1
  • Roberto Sebastiani
    • 2
  1. 1.Fondazione Bruno KesslerTrentoItaly
  2. 2.University of TrentoTrentoItaly

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