Systematic Review of Bug Report Processing Techniques to Improve Software Management Performance

Dong-Gun Lee and Yeong-Seok Seo
Volume: 15, No: 4, Page: 967 ~ 985, Year: 2019
10.3745/JIPS.04.0130
Keywords: Bug Report, Clustering, Duplication Detection, Information Retrieval, Machine Learning, Priority, Severity, Software Developer Assignment, Software Management, Triage
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Abstract
Bug report processing is a key element of bug fixing in modern software maintenance. Bug reports are not processed immediately after submission and involve several processes such as bug report deduplication and bug report triage before bug fixing is initiated; however, this method of bug fixing is very inefficient because all these processes are performed manually. Software engineers have persistently highlighted the need to automate these processes, and as a result, many automation techniques have been proposed for bug report processing; however, the accuracy of the existing methods is not satisfactory. Therefore, this study focuses on surveying to improve the accuracy of existing techniques for bug report processing. Reviews of each method proposed in this study consist of a description, used techniques, experiments, and comparison results. The results of this study indicate that research in the field of bug deduplication still lacks and therefore requires numerous studies that integrate clustering and natural language processing. This study further indicates that although all studies in the field of triage are based on machine learning, results of studies on deep learning are still insufficient.

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Cite this article
IEEE Style
D. L. Y. Seo, "Systematic Review of Bug Report Processing Techniques to Improve Software Management Performance," Journal of Information Processing Systems, vol. 15, no. 4, pp. 967~985, 2019. DOI: 10.3745/JIPS.04.0130.

ACM Style
Dong-Gun Lee and Yeong-Seok Seo. 2019. Systematic Review of Bug Report Processing Techniques to Improve Software Management Performance, Journal of Information Processing Systems, 15, 4, (2019), 967~985. DOI: 10.3745/JIPS.04.0130.