On the Need of Removing Last Releases of Data When Using or Validating Defect Prediction Models

Aalok Ahluwalia, Massimiliano Di Penta, Davide Falessi

To develop and train defect prediction models, researchers rely on datasets in which a defect is attributed to an artifact, e.g., a class of a given release. However, the creation…