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Towards Using Structural Abstraction for Model Checking

  • Christoph Luckeneder
  • , Ralph Hoch*
  • , Hermann Kaindl
  • *Corresponding author for this work

Publication: Chapter in book/Conference proceedingContribution to conference proceedings

Abstract

Model checking is a method for formally verifying whether defined properties hold for a behavioral model of a system. With increasing complexity of these models, combinatorial explosion may arise. This problem can be addressed by a well-known approach to behavioral abstraction, employed, e.g., in CEGAR. These abstractions need to be over-approximations in the sense of enriching the behavior of the system, to ensure that correctness at the abstract level implies correctness of the original system. However, structural models, which the behaviors operate on, have not yet been considered when applying abstraction operations for model checking.We propose to use structural models as an essential part for model checking with abstraction operations. In this paper, we present an approach to systematically abstracting structural models, from which behavioral abstractions result, so that the ideas of CEGAR can be adapted for structural abstraction. We model structure using bigraphs, and propose abstraction operations on them.

Original languageEnglish
Title of host publicationProceedings - 2023 10th International Conference on Dependable Systems and Their Applications, DSA 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages105-113
Number of pages9
ISBN (Electronic)979-8-3503-0477-0
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event10th International Conference on Dependable Systems and Their Applications, DSA 2023 - Tokyo, Japan
Duration: 10 Aug 202311 Aug 2023

Conference

Conference10th International Conference on Dependable Systems and Their Applications, DSA 2023
Country/TerritoryJapan
CityTokyo
Period10/08/2311/08/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • Bigraph
  • CEGAR
  • Model Checking
  • Over-approximation
  • Structural Abstraction

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