Finding near-optimal configurations in product lines by random sampling

Jeho Oh, Don S. Batory, Margaret Myers, Norbert Siegmund

Abstract

Software Product Lines (SPLs) are highly configurable systems. This raises the challenge to find optimal performing configurations for an anticipated workload. As SPL configuration spaces are huge, it is infeasible to benchmark all configurations to find an optimal one. Prior work focused on building performance models to predict and optimize SPL configurations. Instead, we randomly sample and recursively search a configuration space directly to find near-optimal configurations without constructing a prediction model. Our algorithms are simpler and have higher accuracy and efficiency.

BibTeX

@inproceedings{Oh-al:FSE17,
  author    = {Jeho Oh and
               Don S. Batory and
               Margaret Myers and
               Norbert Siegmund},
  title     = {Finding near-optimal configurations in product lines by random sampling},
  booktitle = {{ESEC/SIGSOFT} {FSE}},
  pages     = {61--71},
  publisher = {{ACM}},
  year      = {2017},
}

Finding near-optimal configurations in product lines by random sampling

Abstract

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