Privacy and utility for defect prediction: Experiments with MORPH

  title={Privacy and utility for defect prediction: Experiments with MORPH},
  author={Fayola Peters and T. Menzies},
  journal={2012 34th International Conference on Software Engineering (ICSE)},
  • Fayola Peters, T. Menzies
  • Published 2012
  • Computer Science
  • 2012 34th International Conference on Software Engineering (ICSE)
Ideally, we can learn lessons from software projects across multiple organizations. However, a major impediment to such knowledge sharing are the privacy concerns of software development organizations. This paper aims to provide defect data-set owners with an effective means of privatizing their data prior to release. We explore MORPH which understands how to maintain class boundaries in a data-set. MORPH is a data mutator that moves the data a random distance, taking care not to cross class… Expand
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