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LTL satisfiability checking

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Abstract

We report here on an experimental investigation of LTL satisfiability checking via a reduction to model checking. By using large LTL formulas, we offer challenging model-checking benchmarks to both explicit and symbolic model checkers. For symbolic model checking, we use CadenceSMV, NuSMV, and SAL-SMC. For explicit model checking, we use SPIN as the search engine, and we test essentially all publicly available LTL translation tools. Our experiments result in two major findings. First, most LTL translation tools are research prototypes and cannot be considered industrial quality tools. Second, when it comes to LTL satisfiability checking, the symbolic approach is clearly superior to the explicit approach.

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Authors and Affiliations

  1. NASA Ames Research Center, Moffett Field, CA, 94035, USA

    Kristin Y. Rozier

  2. Rice University, Houston, TX, 77005, USA

    Moshe Y. Vardi

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  1. Kristin Y. Rozier
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  2. Moshe Y. Vardi
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Correspondence to Kristin Y. Rozier.

Additional information

An earlier version of this paper appeared in SPIN’07.

Work contributing to this paper was completed at Rice University, Cambridge University, and NASA, and was supported in part by the Rice Computational Research Cluster (Ada), funded by NSF under Grant CNS-0421109 and a partnership between Rice University, AMD and Cray.

The use of names of software tools in this report is for accurate reporting and does not constitute an official endorsement, either expressed or implied, of such software by the National Aeronautics and Space Administration.

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Rozier, K.Y., Vardi, M.Y. LTL satisfiability checking. Int J Softw Tools Technol Transfer 12, 123–137 (2010). https://doi.org/10.1007/s10009-010-0140-3

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