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Compositional Static Value Analysis for Higher-Order Numerical Programs (Artifact)

Authors Milla Valnet , Raphaël Monat , Antoine Miné

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DARTS.11.2.5.pdf
  • Filesize: 0.57 MB
  • 5 pages

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Subject Classification

ACM Subject Classification
  • Software and its engineering → Automated static analysis
  • Theory of computation → Program analysis
  • Software and its engineering → Functional languages
Keywords
  • Static Value Analysis
  • Functional Programming
  • Abstract Interpretation

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Artifact

Artifact Evaluation Policy

The artifact has been evaluated as described in the ECOOP 2025 Call for Artifacts and the ACM Artifact Review and Badging Policy.

Abstract

This artifact accompanies the submission entitled "Compositional Static Value Analysis for Higher-Order Numerical Programs". It enables to reproduce experimental claims made in the paper. The artifact requires a computer with Docker installed.

Cite As Get BibTex

Milla Valnet, Raphaël Monat, and Antoine Miné. Compositional Static Value Analysis for Higher-Order Numerical Programs (Artifact). In Special Issue of the 39th European Conference on Object-Oriented Programming (ECOOP 2025). Dagstuhl Artifacts Series (DARTS), Volume 11, Issue 2, pp. 5:1-5:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/DARTS.11.2.5

Author Details

Milla Valnet
  • LIP6, Sorbonne Université, F-75005, Paris, France
Raphaël Monat
  • Univ. Lille, Inria, CNRS, Centrale Lille, UMR 9189 CRIStAL, F-59000 Lille, France
Antoine Miné
  • LIP6, Sorbonne Université, F-75005, Paris, France

Related Article

  • Milla Valnet, Raphaël Monat, and Antoine Miné, "Compositional Static Value Analysis for Higher-Order Numerical Programs", in 39th European Conference on Object-Oriented Programming (ECOOP 2025), LIPIcs, Vol. 333, pp. 32:1-32:29, 2025. https://doi.org/10.4230/LIPIcs.ECOOP.2025.32

References

  1. Pierre Lermusiaux and Benoît Montagu. Detection of uncaught exceptions in functional programs by abstract interpretation. In European Symposium on Programming, pages 391-420. Springer, 2024. URL: https://doi.org/10.1007/978-3-031-57267-8_15.
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