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Selective path-sensitive interval analysis (WIP paper)

Published:22 June 2021Publication History

ABSTRACT

K-limited path-sensitive interval domain is an abstract domain that has been proposed for precise and scalable analysis of large software systems. The domain maintains variables’ value ranges in the form of intervals along a configurable K subsets of paths at each program point, which implicitly provides co-relation among variables. When the number of paths at the join point exceeds K, the set of paths are partitioned into K subsets, arbitrarily, which results in loss of precision required to verify program properties. To address this problem, we propose selective merging of paths - identify and merge paths in such a way that the intervals computed help verifying more properties. Our selective path-sensitive approach is based on the knowledge of variables whose values influence the verification outcomes of program properties. We evaluated our approach on industrial automotive applications as well as academic benchmarks. We show benefits of selective path merging over arbitrary path selection by verifying 40% more properties.

References

  1. 2021. SV-COMP 2021 - 10th International Competition on Software Verification. http://sv-comp.sosy-lab.org/2021/Google ScholarGoogle Scholar
  2. Mohammad Afzal, Supratik Chakraborty, Avriti Chauhan, Bharti Chimdyalwar, Priyanka Darke, Ashutosh Gupta, Shrawan Kumar, Charles Babu, Divyesh Unadkat, and R Venkatesh. 2020. VeriAbs: Verification by Abstraction and Test Generation (Competition Contribution). In International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2020. 383–387. https://doi.org/10.1007/978-3-030-45237-7_25 Google ScholarGoogle ScholarCross RefCross Ref
  3. Astrée. [n.d.]. The Astrée Static Analyzer. http://www.astree.ens.fr/Google ScholarGoogle Scholar
  4. Julien Bertrane, Patrick Cousot, Radhia Cousot, J�r�me Feret, Laurent Mauborgne, Antoine Min�, and Xavier Rival. 2015. Static Analysis and Verification of Aerospace Software by Abstract Interpretation. Foundations and Trends in Programming Languages, 2, 2-3 (2015), https://doi.org/10.1561/2500000002 Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Dirk Beyer, Thomas A. Henzinger, Ranjit Jhala, and Rupak Majumdar. 2007. The Software Model Checker Blast: Applications to Software Engineering. International Journal on Software Tools for Technology Transfer, STTT, 9, 5-6, 505–525. https://doi.org/10.1007/s10009-007-0044-z Google ScholarGoogle ScholarCross RefCross Ref
  6. Gianfranco Bilardi and Keshav Pingali. 1996. A Framework for Generalized Control Dependence. In Proceedings of the ACM SIGPLAN 1996 Conference on Programming Language Design and Implementation (PLDI ’96). ACM, New York, NY, USA. 291–300. isbn:0-89791-795-2 https://doi.org/10.1145/231379.231435 Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Bharti Chimdyalwar and Priyanka Darke. 2018. Statically relating program properties for efficient verification (short WIP paper). In Proceedings of the 19th ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems, LCTES 2018, Philadelphia, PA, USA, June 19-20, 2018, Zheng Zhang and Christophe Dubach (Eds.). ACM, 99–103. https://doi.org/10.1145/3211332.3211341 Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Patrick Cousot and Radhia Cousot. 1977. Abstract Interpretation: A Unified Lattice Model for Static Analysis of Programs by Construction or Approximation of Fixpoints. In Proceedings of the 4th ACM SIGACT-SIGPLAN Symposium on Principles of Programming Languages (POPL ’77). ACM, New York, NY, USA. 238–252. https://doi.org/10.1145/512950.512973 Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. P. Cousot, R. Cousot, J. Feret, L. Mauborgne, A. Miné, D. Monniaux, and X. Rival. 2005. The Astrée Analyzer. In ESOP’05. https://doi.org/10.1007/978-3-540-31987-0_3 Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Facebook. [n.d.]. Infer. https://cacm.acm.org/magazines/2019/8/238344-scaling-static-analyses-at-facebook/fulltextGoogle ScholarGoogle Scholar
  11. Shrawan Kumar, Amitabha Sanyal, and Uday Khedker. 2015. Value Slice: A New Slicing Concept for Scalable Property Checking. In International Conference on Tools and Algorithms for the Construction and Analysis of Systems. 101–115. https://doi.org/10.1007/978-3-662-46681-0_7 Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. MathWorks. [n.d.]. Polyspace Embedded Software Verification. http://www.mathworks.in/products/polyspace/Google ScholarGoogle Scholar
  13. Kumar S., Chimdyalwar B., and Shrotri U.. 2013. Precise range analysis on large industry code. In ESEC/FSE 2013:Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering. ACM, 675–678. https://doi.org/10.1145/2491411.2494569 Google ScholarGoogle ScholarDigital LibraryDigital Library

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    • Published in

      cover image ACM Conferences
      LCTES 2021: Proceedings of the 22nd ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems
      June 2021
      162 pages
      ISBN:9781450384728
      DOI:10.1145/3461648
      • General Chair:
      • Jörg Henkel,
      • Program Chair:
      • Xu Liu

      Copyright © 2021 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 22 June 2021

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