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SMT-Based Verification of Persistency Invariants of Px86 Programs

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Verified Software. Theories, Tools and Experiments. (VSTTE 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13800))

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Abstract

While non-volatile memory (NVM) promises to be both performant and durable, the semantics provided by the hardware architectures are rather subtle and significantly complicate reasoning about the possible observed state after a crash.

Starting from recent persistency extension of the x86 model, we present the first automated approach for proving invariants about the persistent state of bounded NVM programs. Our approach works by encoding the program’s semantics along with its intended invariants into a compact logical formula and querying an SMT solver for its satisfiability. We propose two alternative encodings, which differ in the way the notion of a crash is encoded. For a collection of small to medium-size benchmarks, our implementation is able to detect or prove absence of persistency bugs in time ranging from a couple of seconds to some minutes.

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Notes

  1. 1.

    Khyzha et al. [14] actually present two versions of \(\textrm{DPTSO}_\textrm{syn}\). Throughout this paper we use the second version, which uses the coherence order to define consistency.

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Acknowledgments

We would like to thank the reviewers for their comments. This work was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 101003349).

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Authors and Affiliations

  1. MPI-SWS, Kaiserslautern, Germany

    Iason Marmanis & Viktor Vafeiadis

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  1. Iason Marmanis
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Correspondence to Iason Marmanis .

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Editors and Affiliations

  1. Microsoft Research, Karnataka, India

    Akash Lal

  2. Fondazione Bruno Kessler, Trento, Italy

    Stefano Tonetta

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Marmanis, I., Vafeiadis, V. (2023). SMT-Based Verification of Persistency Invariants of Px86 Programs. In: Lal, A., Tonetta, S. (eds) Verified Software. Theories, Tools and Experiments.. VSTTE 2022. Lecture Notes in Computer Science, vol 13800. Springer, Cham. https://doi.org/10.1007/978-3-031-25803-9_6

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  • DOI: https://doi.org/10.1007/978-3-031-25803-9_6

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