Faster discovery of faster system configurations with spectral learning

@article{Nair2017FasterDO,
  title={Faster discovery of faster system configurations with spectral learning},
  author={Vivek Nair and Tim Menzies and Norbert Siegmund and Sven Apel},
  journal={Automated Software Engineering},
  year={2017},
  volume={25},
  pages={247-277}
}
Despite the huge spread and economical importance of configurable software systems, there is unsatisfactory support in utilizing the full potential of these systems with respect to finding performance-optimal configurations. Prior work on predicting the performance of software configurations suffered from either (a) requiring far too many sample configurations or (b) large variances in their predictions. Both these problems can be avoided using the WHAT spectral learner. WHAT’s innovation is… CONTINUE READING
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