Grammar Based Genetic Programming for Software Configuration Problem
| Autor: | Anna Perini, Jesus Gorronogoitia, Angelo Susi, Denisse Muñante, Fitsum Meshesha Kifetew, Alberto Siena |
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| Rok vydání: | 2017 |
| Předmět: |
Programming language
Computer science business.industry Software development 020207 software engineering 02 engineering and technology computer.software_genre Feature model Inductive programming Software framework Adaptive grammar Software construction 0202 electrical engineering electronic engineering information engineering Programming paradigm 020201 artificial intelligence & image processing Software product line business computer |
| Zdroj: | Search Based Software Engineering ISBN: 9783319662985 SSBSE |
| DOI: | 10.1007/978-3-319-66299-2_10 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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