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Comparing Approaches to Implement Feature Model Composition

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Modelling Foundations and Applications (ECMFA 2010)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 6138))

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Abstract

The use of Feature Models (FMs) to define the valid combinations of features in Software Product Lines (SPL) is becoming commonplace. To enhance the scalability of FMs, support for composing FMs describing different SPL aspects is needed. Some composition operators, with interesting property preservation capabilities, have already been defined but a comprehensive and efficient implementation is still to be proposed. In this paper, we systematically compare strengths and weaknesses of different implementation approaches. The study provides some evidence that using generic model composition frameworks are not helping much in the realization, whereas a specific solution is finally necessary and clearly stands out by its qualities.

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Author information

Authors and Affiliations

  1. I3S Laboratory (CNRS UMR 6070), University of Nice Sophia Antipolis, France

    Mathieu Acher, Philippe Collet & Philippe Lahire

  2. Computer Science Department, Colorado State University, USA

    Robert France

Authors
  1. Mathieu Acher
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  2. Philippe Collet
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  3. Philippe Lahire
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  4. Robert France
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Editor information

Editors and Affiliations

  1. Victoria University, Wellington, New Zealand

    Thomas Kühne

  2. Malina Software Corporation, 10 Blueridge Court, K2J 2J3, Nepean, Ontario, Canada

    Bran Selic

  3. Laboratoire d’Informatique de Paris 6, 8, rue du Capitaine Scott, P.O. Box, 75015, Paris, France

    Marie-Pierre Gervais

  4. CEA LIST, Gif-sur-Yvette, F-91191, France

    François Terrier

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Acher, M., Collet, P., Lahire, P., France, R. (2010). Comparing Approaches to Implement Feature Model Composition. In: Kühne, T., Selic, B., Gervais, MP., Terrier, F. (eds) Modelling Foundations and Applications. ECMFA 2010. Lecture Notes in Computer Science, vol 6138. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13595-8_3

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  • DOI: https://doi.org/10.1007/978-3-642-13595-8_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13594-1

  • Online ISBN: 978-3-642-13595-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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