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ASE 2013

Scalable product line configuration: A straw to break the camel's back

Abdel Salam Sayyad, Joseph Ingram, Tim Menzies, Hany H. Ammar

DOI 10.1109/ase.2013.6693104dblp

Abstract

Software product lines are hard to configure. Techniques that work for medium sized product lines fail for much larger product lines such as the Linux kernel with 6000+ features. This paper presents simple heuristics that help the Indicator-Based Evolutionary Algorithm (IBEA) in finding sound and optimum configurations of very large variability models in the presence of competing objectives. We employ a combination of static and evolutionary learning of model structure, in addition to utilizing a pre-computed solution used as a “seed” in the midst of a randomly-generated initial population. The seed solution works like a single straw that is enough to break the camel's back -given that it is a feature-rich seed. We show promising results where we can find 30 sound solutions for configuring upward of 6000 features within 30 minutes.

BibTeX
@inproceedings{Sayyad-al:ASE13,
  author    = {Abdel Salam Sayyad and
               Joseph Ingram and
               Tim Menzies and
               Hany H. Ammar},
  title     = {Scalable product line configuration: A straw to break the camel's back},
  booktitle = {ASE},
  pages     = {465--474},
  publisher = {{IEEE}},
  year      = {2013},
}

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