On extracting feature models from product descriptions

  • Authors:
  • Mathieu Acher;Anthony Cleve;Gilles Perrouin;Patrick Heymans;Charles Vanbeneden;Philippe Collet;Philippe Lahire

  • Affiliations:
  • University of Namur, Belgium, INRIA Lille-Nord Europe, Université Lille -- LIFL -- CNRS, France;University of Namur, Belgium, INRIA Lille-Nord Europe, Université Lille -- LIFL -- CNRS, France;University of Namur, Belgium, INRIA Lille-Nord Europe, Université Lille -- LIFL -- CNRS, France;University of Namur, Belgium, INRIA Lille-Nord Europe, Université Lille -- LIFL -- CNRS, France;University of Namur, Belgium, INRIA Lille-Nord Europe, Université Lille -- LIFL -- CNRS, France;University of Nice Sophia Antipolis, France;University of Nice Sophia Antipolis, France

  • Venue:
  • Proceedings of the Sixth International Workshop on Variability Modeling of Software-Intensive Systems
  • Year:
  • 2012

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Abstract

In product line engineering, domain analysis is the process of analyzing related products to identify their common and variable features. This process is generally carried out by experts on the basis of existing product descriptions, which are expressed in a more or less structured way. Modeling and reasoning about product descriptions are error-prone and time consuming tasks. Feature models (FMs) constitute popular means to specify product commonalities and variabilities in a compact way, and to provide automated support to the domain analysis process. This paper aims at easing the transition from product descriptions expressed in a tabular format to FMs accurately representing them. This process is parameterized through a dedicated language and high-level directives (e.g., products/features scoping). We guarantee that the resulting FM represents the set of legal feature combinations supported by the considered products and has a readable tree hierarchy together with variability information. We report on our experiments based on public data and characterize the properties of the derived FMs.