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Local Completeness for Program Correctness and Incorrectness (Invited Talk)

Author Roberto Bruni

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Author Details

Roberto Bruni
  • Computer Science Department, University of Pisa, Italy

Funding

Research supported by Italian MIUR PRIN2017 project no. 201784YSZ5 "AnalysiS of PRogram Analyses (ASPRA)", INdAM - GNCS Project, code no. CUP_E53C22001930001 and by a Meta research gift.

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Roberto Bruni. Local Completeness for Program Correctness and Incorrectness (Invited Talk). In 10th Conference on Algebra and Coalgebra in Computer Science (CALCO 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 270, pp. 2:1-2:2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023) https://doi.org/10.4230/LIPIcs.CALCO.2023.2

Abstract

Program correctness techniques aim to prove the absence of bugs, but can yield false alarms because they tend to over-approximate program semantics. Vice versa, program incorrectness methods are aimed to detect true bugs, without false alarms, but cannot be used to prove correctness, because they under-approximate program semantics. In this invited talk we will overview our ongoing research on the use of the abstract interpretation framework to combine under- and over-approximation in the same analysis and distill a logic for program correctness and incorrectness.

Subject Classification

ACM Subject Classification
  • Theory of computation → Logic and verification
  • Theory of computation → Programming logic
  • Theory of computation → Hoare logic
  • Theory of computation → Abstraction
Keywords
  • Program analysis
  • program verification
  • Hoare logic
  • incorrectness logic
  • abstract interpretation
  • local completeness

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References

  1. Flavio Ascari, Roberto Bruni, and Roberta Gori. Limits and difficulties in the design of under-approximation abstract domains. In Proc. of FOSSACS 2022, volume 13242 of LNCS, pages 21-39. Springer, 2022. URL: https://doi.org/10.1007/978-3-030-99253-8_2.
  2. Flavio Ascari, Roberto Bruni, and Roberta Gori. Logics for extensional, locally complete analysis via domain refinements. In Proc. of ESOP 2023, volume 13990 of LNCS, pages 1-27. Springer, 2023. URL: https://doi.org/10.1007/978-3-031-30044-8_1.
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