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Decidability of Resilience for Well-Structured Graph Transformation Systems

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Graph Transformation (ICGT 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13349))

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Abstract

Resilience is a concept of rising interest in computer science and software engineering. For systems in which correctness w.r.t. a safety condition is unachievable, fast recovery is demanded. We ask whether we can reach a safe state in a bounded number of steps whenever we reach a bad state. In a well-structured framework, we investigate problems of this kind where the bad and safety conditions are given as upward/downward-closed sets. We obtain decidability results for graph transformation systems by applying our results for subclasses of well-structured transition systems. Moreover, we identify sufficient criteria of graph transformation systems for the applicability of our results.

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Notes

  1. 1.

    If \(\mathrm {SAFE}\in \mathcal {J}\setminus \mathcal {I}\), our method provides only the answer whether there is a bound k.

  2. 2.

    In [12], “lossy rules” w.r.t. the minor order, i.e., edge contraction rules, are considered in order to obtain well-structuredness for GTSs.

  3. 3.

    The symbol “+” denotes the disjoint union of graphs.

References

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Acknowledgment

I am grateful to Annegret Habel, Nick Würdemann, and the anonymous reviewers for their helpful comments.

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Authors and Affiliations

  1. University of Oldenburg, Oldenburg, Germany

    Okan Özkan

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  1. Okan Özkan
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Correspondence to Okan Özkan .

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Editors and Affiliations

  1. Université Paris Cité, Paris, France

    Nicolas Behr

  2. Computer Science and Engineering, Chalmers | Gothenburg University, Gothenburg, Sweden

    Daniel Strüber

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Özkan, O. (2022). Decidability of Resilience for Well-Structured Graph Transformation Systems. In: Behr, N., Strüber, D. (eds) Graph Transformation. ICGT 2022. Lecture Notes in Computer Science, vol 13349. Springer, Cham. https://doi.org/10.1007/978-3-031-09843-7_3

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  • DOI: https://doi.org/10.1007/978-3-031-09843-7_3

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