Feature Location in Model-Based Software Product Lines Through a Genetic Algorithm

  • Jaime FontEmail author
  • Lorena Arcega
  • Øystein Haugen
  • Carlos Cetina
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9679)


When following an extractive approach to build a model-based Software Product Line (SPL) from a set of existing products, features have to be located across the product models. The approaches that produce best results combine model comparisons with the knowledge from the domain experts to locate the features. However, when the domain expert fails to provide accurate information, the semi-automated approach faces challenges. To cope with this issue we propose a genetic algorithm to feature location in model-based SPLs. We have an oracle from an industrial environment that makes it possible to evaluate the results of the approaches. As a result, the proposed approach is able to provide solutions upon inaccurate information on part of the domain expert while the compared approach fails to provide a solution when the information provided by the domain expert is not accurate enough.


Genetic Algorithm Domain Expert Product Model Software Product Line Mutation Operation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Jaime Font
    • 1
    • 2
    Email author
  • Lorena Arcega
    • 1
    • 2
  • Øystein Haugen
    • 3
  • Carlos Cetina
    • 1
  1. 1.SVIT Research GroupSan Jorge UniversityZaragozaSpain
  2. 2.Department of InformaticsUniversity of OsloOsloNorway
  3. 3.Department of Information TechnologyØstfold University CollegeHaldenNorway

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