Ponencia
Reverse Engineering Feature Models with Evolutionary Algorithms: An Exploratory Study
Autor/es | López Herrejón, Roberto E.
Galindo Duarte, José Ángel Benavides Cuevas, David Felipe Segura Rueda, Sergio Egyed, Alexander |
Departamento | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Fecha de publicación | 2012 |
Fecha de depósito | 2017-05-31 |
Publicado en |
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ISBN/ISSN | 978-3-642-33118-3 0302-9743 |
Resumen | Successful software evolves, more and more commonly, from
a single system to a set of system variants tailored to meet the similiar
and yet di erent functionality required by the distinct clients and
users. Software ... Successful software evolves, more and more commonly, from a single system to a set of system variants tailored to meet the similiar and yet di erent functionality required by the distinct clients and users. Software Product Line Engineering (SPLE) is a software development paradigm that has proven e ective for coping with this scenario. At the core of SPLE is variability modeling which employs Feature Models (FMs) as the de facto standard to represent the combinations of features that distinguish the systems variants. Reverse engineering FMs consist in constructing a feature model from a set of products descriptions. This research area is becoming increasingly active within the SPLE community, where the problem has been addressed with di erent perspectives and approaches ranging from analysis of con guration scripts, use of propositional logic or natural language techniques, to ad hoc algorithms. In this paper, we explore the feasibility of using Evolutionary Algorithms (EAs) to synthesize FMs from the feature sets that describe the system variants. We analyzed 59 representative case studies of di erent characteristics and complexity. Our exploratory study found that FMs that denote proper supersets of the desired feature sets can be obtained with a small number of generations. However, reducing the di erences between these two sets with an e ective and scalable tness function remains an open question.We believe that this work is a rst step towards leveraging the extensive wealth of Search-Based Software Engineering techniques to address this and other variability management challenges. |
Agencias financiadoras | Comisión Interministerial de Ciencia y Tecnología (CICYT). España Junta de Andalucía |
Identificador del proyecto | TIN2009- 07366
TIC-5906 |
Cita | López Herrejón, R.E., Galindo Duarte, J.Á., Benavides Cuevas, D.F., Segura Rueda, S. y Egyed, A. (2012). Reverse Engineering Feature Models with Evolutionary Algorithms: An Exploratory Study. En SSBSE 2012: International Symposium on Search Based Software Engineering (168-182), Riva del Garda, Italy: Springer. |
Ficheros | Tamaño | Formato | Ver | Descripción |
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ssbse2012.pdf | 602.3Kb | [PDF] | Ver/ | |