Heuristics for deriving adaptive homing and distinguishing sequences for nondeterministic finite state machines - Testing Software and Systems Access content directly
Conference Papers Year : 2015

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

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
Fichier principal
Vignette du fichier
385214_1_En_15_Chapter.pdf (187.34 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01262740 , version 1 (17-02-2017)

Licence

Attribution

Identifiers

Cite

Natalia Kushik, Husnu Yenigun. Heuristics for deriving adaptive homing and distinguishing sequences for nondeterministic finite state machines. 27th IFIP International Conference on Testing Software and Systems (ICTSS), Nov 2015, Sharjah And Dubai, United Arab Emirates. pp.243-248, ⟨10.1007/978-3-319-25945-1_15⟩. ⟨hal-01262740⟩
362 View
202 Download

Altmetric

Share

Gmail Facebook X LinkedIn More