Automated analysis of feature models 20 years later: A literature review

By David Benavides, Sergio Segura, Antonio Ruiz-Cortés. Information Systems, 2010

1,297 citations recorded by the source corpus.

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. This paper provides a comprehensive literature review on the automated analysis of feature models 20 years after of their invention. This paper 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 future contributions. We finally discuss the different studies and propose some challenges to be faced in the future.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/7c62fdbfc2baa5dd3e9ab2ac55153dfc9553dda0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

  1. Christian Kästner
  2. Sven Apel
  3. Gunter Saake
  4. Thomas Thüm
  5. Andrzej Wasowski
  6. Ina Schaefer
  7. Krzysztof Czarnecki
  8. Antonio Ruiz-Cortés

In Information Systems

  1. Christian Kästner
  2. Sven Apel
  3. Gunter Saake
  4. Thomas Thüm
  5. Andrzej Wasowski
  6. Ina Schaefer
  7. Krzysztof Czarnecki
  8. Sergio Segura

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