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Effort-aware just-in-time defect identification in practice: a case study at Alibaba

Meng Yan, Xin Xia, Yuanrui Fan, David Lo, Ahmed E. Hassan, Xindong Zhang

Abstract

Effort-aware Just-in-Time (JIT) defect identification aims at identifying defect-introducing changes just-in-time with limited code inspection effort. Such identification has two benefits compared with traditional module-level defect identification, i.e., identifying defects in a more cost-effective and efficient manner. Recently, researchers have proposed various effort-aware JIT defect identification approaches, including supervised (e.g., CBS+, OneWay) and unsupervised approaches (e.g., LT and Code Churn). The comparison of the effectiveness between such supervised and unsupervised approaches has attracted a large amount of research interest. However, the effectiveness of the recently proposed approaches and the comparison among them have never been investigated in an industrial setting.

BibTeX
@inproceedings{Yan-al:FSE20,
  author    = {Meng Yan and
               Xin Xia and
               Yuanrui Fan and
               David Lo and
               Ahmed E. Hassan and
               Xindong Zhang},
  title     = {Effort-aware just-in-time defect identification in practice: a case study at Alibaba},
  booktitle = {{ESEC/SIGSOFT} {FSE}},
  pages     = {1308--1319},
  publisher = {{ACM}},
  year      = {2020},
}

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