4.5 Article

Evolving feature model configurations in software product lines

Journal

JOURNAL OF SYSTEMS AND SOFTWARE
Volume 87, Issue -, Pages 119-136

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jss.2013.10.010

Keywords

Software product line; Feature model; Multi-step configuration

Funding

  1. National Science Foundation (NSF)
  2. Air Force Research Lab (AFRL RI)
  3. European commission (FEDER)
  4. Spanish government under TAPAS [TIN2012-32273]
  5. Andalusian government under Talentia program
  6. Andalusian government under THEOS projects [TIC-5906]

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The increasing complexity and cost of software-intensive systems has led developers to seek ways of reusing software components across development projects. One approach to increasing software reusability is to develop a software product-line (SPL), which is a software architecture that can be reconfigured and reused across projects. Rather than developing software from scratch for a new project, a new configuration of the SPL is produced. It is hard, however, to find a configuration of an SPL that meets an arbitrary requirement set and does not violate any configuration constraints in the SPL. Existing research has focused on techniques that produce a configuration of an SPL in a single step. Budgetary constraints or other restrictions, however, may require multi-step configuration processes. For example, an aircraft manufacturer may want to produce a series of configurations of a plane over a span of years without exceeding a yearly budget to add features. This paper provides three contributions to the study of multi-step configuration for SPLs. First, we present a formal model of multi-step SPL configuration and map this model to constraint satisfaction problems (CSPs). Second, we show how solutions to these SPL configuration problems can be automatically derived with a constraint solver by mapping them to CSPs. Moreover, we show how feature model changes can be mapped to our approach in a multi-step scenario by using feature model drift. Third, we present empirical results demonstrating that our CSP-based reasoning technique can scale to SPL models with hundreds of features and multiple configuration steps. (C) 2013 Elsevier Inc. All rights reserved.

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