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Stochastic Local Search for Solving Floating-Point Constraints

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Numerical Software Verification (NSV 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11652))

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Abstract

We present OL1V3R, a solver for the SMT floating-point theory that is based on stochastic local search (SLS). We adapt for OL1V3R the key ingredients of related work on leveraging SLS to solve the SMT fixed-sized bit-vector theory, and confirm its effectiveness by comparing it with mature solvers. Finally, we discuss the limitations of OL1V3R and propose solutions to make it more powerful.

Supported in part by the National Science Foundation (NSF) awards CCF 1552975 and CCF 1704715.

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Notes

  1. 1.

    We made OL1V3R publicly available at https://github.com/soarlab/OL1V3R.

  2. 2.

    The floating-point formats supported by OL1V3R depend on the capabilities of the underlying “bigfloat” library it employs to evaluate floating-point arithmetic.

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Acknowledgements

We thank Dan Liew for answering our questions related to his work on JFS.

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Authors and Affiliations

  1. School of Computing, University of Utah, Salt Lake City, USA

    Shaobo He, Marek Baranowski & Zvonimir Rakamarić

Authors
  1. Shaobo He
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  2. Marek Baranowski
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  3. Zvonimir Rakamarić
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Corresponding author

Correspondence to Shaobo He .

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Editors and Affiliations

  1. University of Colorado Boulder, Boulder, CO, USA

    Majid Zamani

  2. Max Planck Institute for Software Systems, Kaiserslautern, Germany

    Damien Zufferey

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He, S., Baranowski, M., Rakamarić, Z. (2019). Stochastic Local Search for Solving Floating-Point Constraints. In: Zamani, M., Zufferey, D. (eds) Numerical Software Verification. NSV 2019. Lecture Notes in Computer Science(), vol 11652. Springer, Cham. https://doi.org/10.1007/978-3-030-28423-7_5

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  • DOI: https://doi.org/10.1007/978-3-030-28423-7_5

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  • Online ISBN: 978-3-030-28423-7

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