/sbrbench

Primary LanguagePython

sbrbench

  1. We improve the label correctness of five publicly available SBR (Security bug report) prediction datasets: Ambari, Camel, Derby, Wicket, and Chromium. We manually analyze each bug report, and recall 749 SBRs, which are originally mislabeled as Non-SBRs (NSBRs).

  2. We evaluate the impact of data label correctness on SBR prediction models.

Contact

Xiaoxue Wu (Data maintainer): wuxiaoxue00@gmail.com Wei Zheng: wzheng@nwpu.edu.cn Xin Xia: xxia@zju.edu.cn

Acknowledgements

The following members provide efforts for our manual data annotation (in no particular order):

  • Sensen Guo
  • Zhong Liu
  • Weiqiang Fu
  • Fengyu Liu
  • Manqing Zhang
  • Xiaoxue Wu