• DocumentCode
    54601
  • Title

    A Scalable Approach to Exact Model and Commonality Counting for Extended Feature Models

  • Author

    Fernandez-Amoros, David ; Heradio, Ruben ; Cerrada, Jose A. ; Cerrada, Carlos

  • Author_Institution
    Dept. of Languages & Comput. Syst., Spanish Open Univ. (UNED), Madrid, Spain
  • Volume
    40
  • Issue
    9
  • fYear
    2014
  • fDate
    Sept. 1 2014
  • Firstpage
    895
  • Lastpage
    910
  • Abstract
    A software product line is an engineering approach to efficient development of software product portfolios. Key to the success of the approach is to identify the common and variable features of the products and the interdependencies between them, which are usually modeled using feature models. Implicitly, such models also include valuable information that can be used by economic models to estimate the payoffs of a product line. Unfortunately, as product lines grow, analyzing large feature models manually becomes impracticable. This paper proposes an algorithm to compute the total number of products that a feature model represents and, for each feature, the number of products that implement it. The inference of both parameters is helpful to describe the standardization/parameterization balance of a product line, detect scope flaws, assess the product line incremental development, and improve the accuracy of economic models. The paper reports experimental evidence that our algorithm has better runtime performance than existing alternative approaches.
  • Keywords
    software engineering; software product lines; commonality counting; extended feature models; product line incremental development; software product line; software product portfolio development; Analytical models; Computational modeling; Economics; Frequency modulation; Headphones; Portfolios; Software; Feature models; economic models; formal methods; software product lines;
  • fLanguage
    English
  • Journal_Title
    Software Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0098-5589
  • Type

    jour

  • DOI
    10.1109/TSE.2014.2331073
  • Filename
    6835200