Grammar Based Genetic Programming for Software Configuration Problem

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Kifetew:2017:SSBSE,

• author = "Fitsum Meshesha Kifetew and Denisse Munante and Jesus Gorronogoitia and Alberto Siena and Angelo Susi and Anna Perini",
• title = "Grammar Based Genetic Programming for Software Configuration Problem",
• booktitle = "Proceedings of the 9th International Symposium on Search Based Software Engineering, SSBSE 2017",
• year = "2017",
• editor = "Tim Menzies and Justyna Petke",
• volume = "10452",
• series = "LNCS",
• pages = "130--136",
• address = "Paderborn, Germany",
• month = sep # " 9-11",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, SBSE, NSGA-II, Grammar Feature model Software product line",
• isbn13 = "978-3-319-66299-2",
• DOI = "doi:10.1007/978-3-319-66299-2_10",
• size = "7 pages",
• abstract = "Software Product Lines (SPLs) capture commonalities and variability of product families, typically represented by means of feature models. The selection of a set of suitable features when a software product is configured is typically made by exploring the space of tread-offs along different attributes of interest, for instance cost and value. In this paper, we present an approach for optimal product configuration by exploiting feature models and grammar guided genetic programming. In particular, we propose a novel encoding of candidate solutions, based on grammar representation of feature models, which ensures that relations imposed in the feature model are respected by the candidate solutions.",
• notes = "Short Papers http://ssbse17.github.io/ Co-located with FSE/ESEC 2017",

}

Genetic Programming entries for Fitsum Meshesha Kifetew Denisse Yessica Munante Arzapalo Jesus Gorronogoitia Alberto Siena Angelo Susi Anna Perini

Citations