A discriminative model approach for accurate duplicate bug report retrieval

By Chengnian Sun, David Lo, Xiaoyin Wang, Jing Jiang, Siau-cheng Khoo. 2010 ACM/IEEE 32nd International Conference on Software Engineering, 2010

346 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems, Software

View Paper: https://www.semanticscholar.org/paper/ddbec64e25d7db22326b5350110e3f3a283ea6a8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. David Lo
2. Jing Jiang
3. Jian Zhou
4. Hongyu Zhang

In Information Systems

1. Hongyu Zhang
2. David Lo
3. Siau-cheng Khoo
4. Jing Jiang
5. Jian Zhou
6. Chengnian Sun
7. Xin Ye
8. Chang Liu

In Software

1. Hongyu Zhang
2. David Lo
3. Siau-cheng Khoo
4. Jing Jiang
5. Jian Zhou
6. Chengnian Sun
7. Xin Ye
8. Chang Liu

Citations in the corpus

• RCLinker: Automated Linking of Issue Reports and Commits Leveraging Rich Contextual Information (2015, neutral): “There also a number of techniques that infer missing links between duplicated bug reports [52], [59], [26], [55], [54], [58], [48], [1].”
• Where should the bugs be fixed? More accurate information retrieval-based bug localization based on bug reports (2012, background): “Many researchers mine bug report information to solve software engineering problems such as duplicate bug detection [33, 35], automatic bug triage [4, 7], bug report quality analysis [6, 7], and defect prediction [20, 37].”
• Towards more accurate retrieval of duplicate bug reports (2011, methodology): “Our approach is built upon BM25F model which is studied not long ago in the information retrieval community [8], [9].”