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Software & Systems Modeling

, Volume 14, Issue 1, pp 45–63 | Cite as

TacoFlow: optimizing SAT program verification using dataflow analysis

  • Bruno Cuervo Parrino
  • Juan Pablo Galeotti
  • Diego Garbervetsky
  • Marcelo F. Frias
Special Section Paper

Abstract

In previous work, we presented TACO, a tool for efficient bounded verification. TACO translates programs annotated with contracts to a SAT problem which is then solved resorting to off-the-shelf SAT-solvers. TACO may deem propositional variables used in the description of a program initial states as being unnecessary. Since the worst-case complexity of SAT (a known NP problem) depends on the number of variables, most times this allows us to obtain significant speed ups. In this article, we present TacoFlow, an improvement over TACO that uses dataflow analysis in order to also discard propositional variables that describe intermediate program states. We present an extensive empirical evaluation that considers the effect of removing those variables at different levels of abstraction, and a discussion on the benefits of the proposed approach.

Keywords

SAT-based verification Dataflow analysis Java-like programs verification 

Notes

Acknowledgments

We thank the anonymous reviewers for their insightful comments and suggestions that help us improving the paper. This work is partially supported by PICT-PAE 2278, PICT-1774, PICT-2351, UBACYT W0813, UBACYT 20020110200075, CONICET PIP955, PIP 11220110100596CO, LIA INFINIS, EA ANCOME, and MEALS 295261.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Bruno Cuervo Parrino
    • 1
  • Juan Pablo Galeotti
    • 2
  • Diego Garbervetsky
    • 1
    • 3
  • Marcelo F. Frias
    • 3
    • 4
  1. 1.Departamento de ComputaciónFCEyN, UBABuenos AiresArgentina
  2. 2.Saarland UniversitySaarbrückenGermany
  3. 3.CONICETBuenos AiresArgentina
  4. 4.Department of Software EngineeringInstituto Tecnológico de Buenos AiresBuenos AiresArgentina

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