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The optimisation of stochastic grammars to enable cost-effective probabilistic structural testing
Blekinge Tekniska Högskola, Fakulteten för datavetenskaper, Institutionen för programvaruteknik.
2015 (engelsk)Inngår i: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 103, s. 296-310Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The effectiveness of statistical testing, a probabilistic structural testing strategy, depends on the characteristics of the probability distribution from which test inputs are sampled. Metaheuristic search has been shown to be a practical method of optimising the characteristics of such distributions. However, the applicability of the existing search-based algorithm is limited by the requirement that the software's inputs must be a fixed number of ordinal values. In this paper we propose a new algorithm that relaxes this limitation and so permits the derivation of probability distributions for a much wider range of software. The representation used by the new algorithm is based on a stochastic grammar supplemented with two novel features: conditional production weights and the dynamic partitioning of ordinal ranges. We demonstrate empirically that a search algorithm using this representation can optimise probability distributions over complex input domains and thereby enable costeffective statistical testing, and that the use of both conditional production weights and dynamic partitioning can be beneficial to the search process. (C) 2014 Elsevier Inc. All rights reserved.

sted, utgiver, år, opplag, sider
2015. Vol. 103, s. 296-310
Emneord [en]
Search-based software engineering, Software testing, Grammar-based testing
HSV kategori
Identifikatorer
URN: urn:nbn:se:bth-698DOI: 10.1016/j.jss.2014.11.042ISI: 000351971500020OAI: oai:DiVA.org:bth-698DiVA, id: diva2:814217
Tilgjengelig fra: 2015-05-26 Laget: 2015-05-26 Sist oppdatert: 2018-01-11bibliografisk kontrollert

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