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Lifting the Reasoning Level in Generic Weak Memory Verification

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Integrated Formal Methods (iFM 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14300))

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Abstract

Weak memory models specify the semantics of concurrent programs on multi-core architectures. Reasoning techniques for weak memory models are often specialized to one fixed model and verification results are hence not transferable to other memory models. A recent proposal of a generic verification technique based on axioms on program behaviour expressed via weakest preconditions aims at overcoming this specialization to dedicated models. Due to the usage of weakest preconditions, reasoning however takes place on a very low level requiring the application of numerous axioms for deriving program properties, even for a single statement.

In this paper, we lift reasoning in this generic verification approach to a more abstract level. Based on a view-based assertion language, we provide a number of novel proof rules for directly reasoning on the level of program constructs. We prove soundness of our proof rules and exemplify them on the write-to-read causality (WRC) litmus test. A comparison to the axiom-based low-level proof reveals a significant reduction in the number of required proof steps.

Bargmann and Wehrheim are supported by DFG-WE2290/14-1.

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Notes

  1. 1.

    Such backward substitution is sound here as it only considers local registers.

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Authors and Affiliations

  1. Department of Computing Science, University of Oldenburg, Oldenburg, Germany

    Lara Bargmann & Heike Wehrheim

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  1. Lara Bargmann
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  2. Heike Wehrheim
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Correspondence to Lara Bargmann .

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Editors and Affiliations

  1. Embedded Systems Group, University of Münster, Münster, Germany

    Paula Herber

  2. Eindhoven University of Technology, Eindhoven, The Netherlands

    Anton Wijs

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Bargmann, L., Wehrheim, H. (2024). Lifting the Reasoning Level in Generic Weak Memory Verification. In: Herber, P., Wijs, A. (eds) Integrated Formal Methods. iFM 2023. Lecture Notes in Computer Science, vol 14300. Springer, Cham. https://doi.org/10.1007/978-3-031-47705-8_10

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  • DOI: https://doi.org/10.1007/978-3-031-47705-8_10

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