Correctly Slicing Extended Finite State Machines

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Abstract

We consider slicing extended finite state machines. Extended finite state machines (EFSMs) combine a finite state machine with a store and can model a range of computational phenomena, from high-level software to cyber-physical systems. EFSMs are essentially interactive, possibly non-terminating or with multiple exit states and may be nondeterministic, so standard techniques for slicing, developed for control flow graphs of programs with a functional semantics, are not immediately applicable. This paper addresses the various aspects of correctness for slicing of EFSMs, and provides syntactic criteria that we prove are sufficient for our proposed notions of semantic correctness. The syntactic criteria are based on the “weak commitment” and “strong commitment” properties highlighted by Danicic et alia. We provide polynomial-time algorithms to compute the least sets satisfying each of these two properties. We have conducted experiments using widely-studied benchmark and industrial EFSMs that compare our slicing algorithms with those using existing definitions of control dependence. We found that our algorithms produce the smallest average slices sizes, 21% of the original EFSMs when “weak commitment” is sufficient and 58% when “strong commitment” is needed (to preserve termination properties).

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Amtoft, T., Androutsopoulos, K., & Clark, D. (2020). Correctly Slicing Extended Finite State Machines. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12065 LNCS, pp. 149–197). Springer. https://doi.org/10.1007/978-3-030-41103-9_6

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