Heuristics for deriving adaptive homing and distinguishing sequences for nondeterministic finite state machines

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Abstract

Distinguishing Sequences (DS) and Homing Sequences (HS) are used for state identification purposes in Finite State Machine (FSM) based testing. For deterministic FSMs, DS and HS related problems are well studied, for both preset and adaptive cases. There are also recent algorithms for checking the existence and constructing Adaptive DS and Adaptive HS for nondeterministic FSMs. However, most of the related problems are proven to be PSPACE-complete, while the worst case height of Adaptive DS and HS is known to be exponential. Therefore, novel heuristics and FSM classes where they can be applied need to be provided for effective derivation of such sequences. In this paper, we present a work in progress on the minimization of Adaptive DS and Adaptive HS for nondeterministic FSMs.

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Kushik, N., & Yenigün, H. (2015). Heuristics for deriving adaptive homing and distinguishing sequences for nondeterministic finite state machines. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9447, pp. 243–248). Springer Verlag. https://doi.org/10.1007/978-3-319-25945-1_15

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