A parallel evolutionary algorithm for prioritized pairwise testing of software product lines
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86093025" target="_blank" >RIV/61989100:27240/14:86093025 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1145/2576768.2598305" target="_blank" >http://dx.doi.org/10.1145/2576768.2598305</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/2576768.2598305" target="_blank" >10.1145/2576768.2598305</a>
Alternative languages
Result language
angličtina
Original language name
A parallel evolutionary algorithm for prioritized pairwise testing of software product lines
Original language description
Software Product Lines (SPLs) are families of related software systems, which provide different feature combinations. Different SPL testing approaches have been proposed. However, despite the extensive and successful use of evolutionary computation techniques for software testing, their application to SPL testing remains largely unexplored. In this paper we present the Parallel Prioritized product line Genetic Solver (PPGS), a parallel genetic algorithm for the generation of prioritized pairwise testing suites for SPLs. We perform an extensive and comprehensive analysis of PPGS with 235 feature models from a wide range of number of features and products, using 3 different priority assignment schemes and 5 product prioritization selection strategies. We also compare PPGS with the greedy algorithm prioritized-ICPL. Our study reveals that overall PPGS obtains smaller covering arrays with an acceptable performance difference with prioritized-ICPL. 2014 ACM.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference
ISBN
978-1-4503-2662-9
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
1255-1262
Publisher name
ACM
Place of publication
New York
Event location
Vancouver
Event date
Jul 12, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000364333000157