Automated Analysis of Feature Models 20 Years Later: A Literature Review

• David Benavides ^[1] ; Sergio Segura ^[1] ; Antonio Ruiz-Cortés ^[1]
  1. [1] Universidad de Sevilla

     Universidad de Sevilla

     Sevilla, España

     
• Localización: Actas de las Jornadas de Ingeniería del Software y Bases de Datos (JISBD´11), 2011, ISBN 978-84-9749-486-1, págs. 951-952
• Idioma: inglés
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• Resumen

  • Software product line engineering is about producing a set of related products that share more commonalities than variabilities. Feature models are widely used for variability and commonality management in software product lines. Feature models are information models where a set of products are represented as a set of features in a single model. The automated analysis of feature models deals with the computer-aided extraction of information from feature models. The literature on this topic has contributed with a set of operations, techniques, tools and empirical results which have not been surveyed until now. The paper associated to this contribution provides a comprehensive literature review on the automated analysis of feature models 20 years after of their invention. It contributes by bringing together previously disparate streams of work to help shed light on this thriving area. We also present a conceptual framework to understand the different proposals as well as categorise fu- ture contributions. We finally discuss the different studies and propose some challenges to be faced in the future.Fifty three primary studies were analysed from where we report 30 op- erations of analysis and four different groups of proposals to automate those operations. The main target audience of this literature review are researchers in the field of automated analysis, tool developers or practitioners who are interested in analysis of feature models as well as researchers and professionals of information systems interested in software product lines, their models and analyses.