2026-05-28T19:13:15Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/81952026-02-03T12:05:32Zcom_10630_2254col_10630_37959
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
López-Herrejón, Roberto E.
author
Ferrer-Urbano, Francisco Javier
author
Chicano-García, José-Francisco
author
Haslinger, Evelyn Nicole
author
Eyed, Alexander
author
Alba-Torres, Enrique
2014-10-07T07:06:05Z
2014-10-07T07:06:05Z
2014-10-07
http://hdl.handle.net/10630/8195
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.
eng
Computación evolutiva
A parallel evolutionary algorithm for prioritized pairwise testing of software product lines
conference output
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URL
https://riuma.uma.es/bitstreams/b4101c39-fa7a-4cd0-b9ca-3b062a885ab3/download
File
MD5
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application/pdf
preprint-gecco2014.pdf
URL
https://riuma.uma.es/bitstreams/3d295d15-b942-44ba-87a3-55c56617933b/download
File
MD5
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text/plain
preprint-gecco2014.pdf.txt