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Automated Property Directed Self Composition

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Automated Technology for Verification and Analysis (ATVA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14216))

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Abstract

We consider the problem of hypersafety verification, i.e. of verifying k-safety properties of a program. While this can, in principle, be addressed by self composition, which reduces the k-safety verification task into a standard (\(1-\))safety verification exercise, verifying self-composed programs is not easy. The proofs often require that the functionality of every component program be captured fully, making invariant inference a challenge. Recently, a technique for property directed self composition (or, Pdsc) was proposed to tackle this problem. Pdsc tries to come up with a semantic self-composition function, together with the inductive invariant that is needed to verify the safety of the self-composed program. One of its crucial limitations, however, is that it relies on users to supply a set of predicates in which the composition and the invariant may be expressed. It is quite challenging even for a user to supply such a set of predicates – the set needs to be sufficiently expressive, so that the invariant can be expressed using those predicates (and their boolean combinations), but not overly expressive to increase the search-space unnecessarily. This paper proposes a technique to automate Pdsc fully, by discovering new predicates whenever the given set is found to be insufficient. We present three different approaches for obtaining predicates – relying on syntax-guided synthesis, quantifier elimination, and interpolation – and discuss the strengths and limitations of these.

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Notes

  1. 1.

    Artifacts available at: https://github.com/Akshatha-Shenoy/PdscSynth.

  2. 2.

    https://bitbucket.org/sharonsh/pdsc/src/master/.

  3. 3.

    https://formal.kastel.kit.edu/projects/improve/reve/.

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Author information

Authors and Affiliations

  1. TCS Research, Pune, India

    Akshatha Shenoy & Sumanth Prabhu

  2. Indian Institute of Technology Delhi, New Delhi, India

    Kumar Madhukar

  3. Mend.io, Tel Aviv, Israel

    Ron Shemer

  4. Chennai Mathematical Institute, Chennai, India

    Mandayam Srivas

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  1. Akshatha Shenoy
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  2. Sumanth Prabhu
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  3. Kumar Madhukar
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  4. Ron Shemer
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  5. Mandayam Srivas
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Correspondence to Akshatha Shenoy .

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Editors and Affiliations

  1. Université Sorbonne Paris Nord, Villetaneuse, France

    Étienne André

  2. Singapore Management University, Singapore, Singapore

    Jun Sun

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Shenoy, A., Prabhu, S., Madhukar, K., Shemer, R., Srivas, M. (2023). Automated Property Directed Self Composition. In: André, É., Sun, J. (eds) Automated Technology for Verification and Analysis. ATVA 2023. Lecture Notes in Computer Science, vol 14216. Springer, Cham. https://doi.org/10.1007/978-3-031-45332-8_7

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  • DOI: https://doi.org/10.1007/978-3-031-45332-8_7

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