Volume 9 Number 12 (Dec. 2014)
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JSW 2014 Vol.9(12): 3035-3040 ISSN: 1796-217X
doi: 10.4304/jsw.9.12.3035-3040

Novel Metrics for Bug Triage

V. Akila and G. Zayaraz

Dept. of Computer Science and Engineering, Pondicherry EngineeringCollege,Pondicherry, India

Abstract—Bug Triaging is a vital part of issue management systems. Bug triaging deals with assigning a developer the task of an incoming bug. This activity is error prone and time consuming if done manually. There is a need for automated support to accelerate this process. The current automated bug triaging systems exploits the text contents of the bug and the tossing relations among the developers. The automated bug triaging systems estimate the optimal bath between the first assignee of the bug and the bug resolver using the tossing relations. The metrics used for assessing the efficiency of bug triaging systems that are based on tossing relations is Mean number of Steps To Resolve (MSTR). This metric quantifies the number of steps reduced by the predicted path compared to the original path. It does not capture how far the retrieved path is in alignment with the actual path. MSTR does reveal the information regarding the extent to which the order of the developers in the retrieved path is in line with that of the original path. In addition, there are no indicators for measuring the strength of the retrieved path. In this paper, we propose two metrics (i) Path Similarity Metric which quantifies path alignment based on pair wise path alignment and (ii) Path Alignment Indicator that measures the effectiveness of the retrieved path based on degree centrality. The effectiveness of the two proposed metrics is validated using bug reports extracted from the Eclipse project.

Index Terms—Open Source Software, Bug Triaging, Mean Steps To Resolve

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Cite: V. Akila and G. Zayaraz, "Novel Metrics for Bug Triage," Journal of Software vol. 9, no. 12, pp. 3035-3040, 2014.

General Information

ISSN: 1796-217X (Online)
Frequency:  Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsweditorialoffice@gmail.com
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