Mining Severe Priority Bugs in Software Maintenance
Satish C J1, Thendral Puyalnithi2
1Satish C J, Department of Computer Science and Engineering, Vellore Institute of Technology, Vellore (Tamil Nadu), India.
2Thendral Puyalnithi, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
Manuscript received on 02 December 2019 | Revised Manuscript received on 20 December 2019 | Manuscript Published on 31 December 2019 | PP: 729-732 | Volume-8 Issue-4S2 December 2019 | Retrieval Number: D11301284S219/2019©BEIESP | DOI: 10.35940/ijrte.D1130.1284S219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Maintenance of open source software is a hectic task as the number of bugs reported is huge. The number of projects, components and versions in an open source project also contribute to the number of bugs that are being reported. Classification of bugs based on priority and identification of the suitable engineers for assignment of bugs for such huge systems still remains a major challenge. Bugs that are misclassified or assigned to engineers who don’t have the component expertise, drastically affect the time taken towards bug resolution. In this paper we have explored the usage of data mining techniques on the classification of bugs and assignment of bugs to engineers.Our focus was on classifying bugs as either severe or non-severe and identification of engineers who have the right expertise to fix the bugs. The prediction of bug severity and identification of engineers were done by mining bug reports from JIRA, an open source software bug tracking tool. The mining process yielded positive results and will be a decision enhancer for severe bugs in the maintenance phase.
Keywords: Mining Software Repository, Data Mining, Software Maintenance.
Scope of the Article: Software Engineering & Its Applications