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Bug Triage Automation Approaches: A Comparative Study

Bug Triage Automation Approaches: A Comparative Study

Madonna Fanoos, Abeer Hamdy, Khaled A. Nagaty
Copyright: © 2022 |Volume: 13 |Issue: 1 |Pages: 19
ISSN: 1942-3926|EISSN: 1942-3934|EISBN13: 9781683180975|DOI: 10.4018/IJOSSP.313183
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MLA

Fanoos, Madonna, et al. "Bug Triage Automation Approaches: A Comparative Study." IJOSSP vol.13, no.1 2022: pp.1-19. http://doi.org/10.4018/IJOSSP.313183

APA

Fanoos, M., Hamdy, A., & Nagaty, K. A. (2022). Bug Triage Automation Approaches: A Comparative Study. International Journal of Open Source Software and Processes (IJOSSP), 13(1), 1-19. http://doi.org/10.4018/IJOSSP.313183

Chicago

Fanoos, Madonna, Abeer Hamdy, and Khaled A. Nagaty. "Bug Triage Automation Approaches: A Comparative Study," International Journal of Open Source Software and Processes (IJOSSP) 13, no.1: 1-19. http://doi.org/10.4018/IJOSSP.313183

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Abstract

Bug triage is an essential task in the software maintenance phase. It is the process of assigning a developer (fixer) to a bug report. A personnel (triager) has to analyze the developers' profiles and bug reports for the purpose of making a suitable assignment. Manual bug triage consumes time and effort, so automating this process is a necessity. The previous research studies addressed the triage problem as an information retrieval problem, where the new bug report is the query. Other researchers tackled this problem as a classification problem and utilized traditional machine learning or deep learning techniques. A handful of research studies handled this problem as an optimization problem and utilized optimization algorithms such as Hungarian. This paper briefs and analyzes the previous bug triage approaches in addition to conducting an empirical comparison among five of the previous approaches.

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