Ebrahimi, Neda, Trabelsi, Abdelaziz, Islam, Md. Shariful, Hamou-Lhadj, Abdelwahab and Khanmohammadi, Kobra (2019) An HMM-based approach for automatic detection and classification of duplicate bug reports. Information and Software Technology . ISSN 09505849 (In Press)
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Official URL: http://dx.doi.org/10.1016/j.infsof.2019.05.007
Abstract
Software projects rely on their issue tracking systems to guide maintenance activities of software developers. Bug reports submitted to the issue tracking systems carry crucial information about the nature of the crash (such as texts from users or developers and execution information about the running functions before the occurrence of a crash). Typically, big software projects receive thousands of reports every day.
| Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering |
|---|---|
| Item Type: | Article |
| Refereed: | Yes |
| Authors: | Ebrahimi, Neda and Trabelsi, Abdelaziz and Islam, Md. Shariful and Hamou-Lhadj, Abdelwahab and Khanmohammadi, Kobra |
| Journal or Publication: | Information and Software Technology |
| Date: | 14 May 2019 |
| Funders: |
|
| Digital Object Identifier (DOI): | 10.1016/j.infsof.2019.05.007 |
| Keywords: | Duplicate bug reports; Stack traces; Hidden Markov models; Machine learning; Mining software repositories |
| ID Code: | 985443 |
| Deposited By: | Monique Lane |
| Deposited On: | 03 Jun 2019 18:40 |
| Last Modified: | 14 May 2021 01:00 |
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