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Matching Plans for Frame Inference in Compositional Reasoning

Authors Andreas Lööw, Daniele Nantes-Sobrinho, Sacha-Élie Ayoun, Petar Maksimović, Philippa Gardner

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Author Details

Andreas Lööw
  • Imperial College London, UK
Daniele Nantes-Sobrinho
  • Imperial College London, UK
Sacha-Élie Ayoun
  • Imperial College London, UK
Petar Maksimović
  • Imperial College London, UK
  • Runtime Verification Inc., Chicago, IL, USA
Philippa Gardner
  • Imperial College London, UK

Funding

This work was supported by the EPSRC Fellowship "VetSpec: Verified Trustworthy Software Specification" (EP/R034567/1).

Acknowledgements

We would like to thank José Fragoso Santos, who conceived the idea of matching plans (which we formalise in this work) as part of the work on JaVerT [Fragoso Santos et al., 2019] and did their original implementation in Gillian. We would also like to thank the anonymous reviewers for their comments.

Cite AsGet BibTex

Andreas Lööw, Daniele Nantes-Sobrinho, Sacha-Élie Ayoun, Petar Maksimović, and Philippa Gardner. Matching Plans for Frame Inference in Compositional Reasoning. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 26:1-26:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.ECOOP.2024.26

Abstract

The use of function specifications to reason about function calls and the manipulation of user-defined predicates are two essential ingredients of modern compositional verification tools based on separation logic. To execute these operations successfully, these tools must be able to solve the frame inference problem, that is, to understand which parts of the state are relevant for the operation at hand. We introduce matching plans, a concept that is used in the Gillian verification platform to automate frame inference efficiently. We extract matching plans and their automation machinery from the Gillian implementation and present them in a tool-agnostic way, making the Gillian approach available to the broader verification community as a verification-tool design pattern.

Subject Classification

ACM Subject Classification
  • Theory of computation → Logic and verification
  • Theory of computation → Separation logic
  • Theory of computation → Automated reasoning
Keywords
  • Compositional reasoning
  • separation logic
  • frame inference

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References

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