Abstract
Recursive state machines (RSMs) are state-based models for procedural programs with wide-ranging applications in program verification and interprocedural analysis. Model-checking algorithms for RSMs and related formalisms and various temporal logic specifications have been intensively studied in the literature.
In this paper, we devise a new model-checking algorithm for RSMs and requirements in computation tree logic (CTL) that exploits the compositional structure of RSMs by ternary model checking in combination with a lazy evaluation scheme. Specifically, a procedural component is only analyzed in those cases in which it might influence the satisfaction of the CTL requirement. We evaluate our prototypical implementation on randomized scalability benchmarks and on an interprocedural data-flow analysis of Java programs, showing both practical applicability and significant speedups in comparison to state-of-the-art model-checking tools for procedural programs.
The authors are supported by the DFG through the Cluster of Excellence EXC 2050/1 (CeTI, project ID 390696704, as part of Germany’s Excellence Strategy) and the TRR 248 (see https://perspicuous-computing.science, project ID 389792660).
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Notes
- 1.
The tool along with data to reproduce our experimental studies can be downloaded at https://github.com/PattuX/RSMCheck.
- 2.
Since the standard CTL model-checking deduction follows a backward-search approach, the contextual information contained in the exit nodes of the component propagates towards the entry nodes of the component during a local deduction step.
- 3.
This is done due to better understandability of the approach. For practical implementations, one might only copy and modify interpretations on the components.
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Dubslaff, C., Wienhöft, P., Fehnker, A. (2021). Be Lazy and Don’t Care: Faster CTL Model Checking for Recursive State Machines. In: Calinescu, R., Păsăreanu, C.S. (eds) Software Engineering and Formal Methods. SEFM 2021. Lecture Notes in Computer Science(), vol 13085. Springer, Cham. https://doi.org/10.1007/978-3-030-92124-8_19
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