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Bit-Precise Reasoning via Int-Blasting

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Verification, Model Checking, and Abstract Interpretation (VMCAI 2022)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 13182))

Abstract

The state of the art for bit-precise reasoning in the context of Satisfiability Modulo Theories (SMT) is a SAT-based technique called bit-blasting where the input formula is first simplified and then translated to an equisatisfiable propositional formula. The main limitation of this technique is scalability, especially in the presence of large bit-widths and arithmetic operators. We introduce an alternative technique, which we call int-blasting, based on a translation to an extension of integer arithmetic rather than propositional logic. We present several translations, discuss their differences, and evaluate them on benchmarks that arise from the verification of rewrite rule candidates for bit-vector solving, as well as benchmarks from SMT-LIB. We also provide preliminary results on 35 benchmarks that arise from smart contract verification. The evaluation shows that this technique is particularly useful for benchmarks with large bit-widths and can solve benchmarks that the state of the art cannot.

This work was supported in part by DARPA (awards N66001-18-C-4012, FA8650-18-2-7854 and FA8650-18-2-7861), ONR (award N68335-17-C-0558), the Stanford Center for Blockchain Research, Certora Inc., and by an NSF Graduate Fellowship (to Makai Mann).

A. Irfan—This author’s contributions were made while he was a postdoc at Stanford University.

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Notes

  1. 1.

    The result of this modulo operation is non-negative, even when the argument is negative, as specified by the SMT-LIB 2 standard.

  2. 2.

    An artifact that includes the implementation, benchmarks, and results is available at https://doi.org/10.5281/zenodo.5652826.

  3. 3.

    Provided to us by collaborators at Certora.

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Authors and Affiliations

  1. Bar-Ilan University, Ramat Gan, Israel

    Yoni Zohar

  2. Stanford University, Stanford, USA

    Ahmed Irfan, Makai Mann, Aina Niemetz, Andres Nötzli, Mathias Preiner & Clark Barrett

  3. The University of Iowa, Iowa City, USA

    Andrew Reynolds & Cesare Tinelli

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  1. Yoni Zohar
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  2. Ahmed Irfan
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  3. Makai Mann
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Correspondence to Yoni Zohar .

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  1. Helmholtz Center for Information Security, Saarbrücken, Germany

    Bernd Finkbeiner

  2. New York University, New York, NY, USA

    Thomas Wies

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Zohar, Y. et al. (2022). Bit-Precise Reasoning via Int-Blasting. In: Finkbeiner, B., Wies, T. (eds) Verification, Model Checking, and Abstract Interpretation. VMCAI 2022. Lecture Notes in Computer Science(), vol 13182. Springer, Cham. https://doi.org/10.1007/978-3-030-94583-1_24

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  • DOI: https://doi.org/10.1007/978-3-030-94583-1_24

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