Abstract
We address the verification of timed concurrent systems with unknown or uncertain constants considered as parameters. First, we introduce parametric event-recording automata (PERAs), as a new subclass of parametric timed automata (PTAs). Although in the non-parametric setting event-recording automata yield better decidability results than timed automata, we show that the most common decision problem remains undecidable for PERAs. Then, given one set of components with parameters and one without, we propose a method to compute an abstraction of the non-parametric set of components, so as to improve the verification of reachability properties in the full (parametric) system. We also show that our method can be extended to general PTAs. We implemented our method, which shows promising results.
This work is partially supported by the ANR national research program “PACS” (ANR-14-CE28-0002).
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Notes
- 1.
Sources, binaries, models and results are available at imitator.fr/static/FORTE17.
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Acknowledgment
We warmly thank Lăcrămioara Aştefănoaei for her appreciated help with installing and using the prototype tool of [9].
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André, É., Lin, SW. (2017). Learning-Based Compositional Parameter Synthesis for Event-Recording Automata. In: Bouajjani, A., Silva, A. (eds) Formal Techniques for Distributed Objects, Components, and Systems. FORTE 2017. Lecture Notes in Computer Science(), vol 10321. Springer, Cham. https://doi.org/10.1007/978-3-319-60225-7_2
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