A New Method to Evaluate Bug Severity by using the Crowd-based Knowledge
Yiwen, W., Yang, Z. (2016). A New Method to Evaluate Bug Severity by using the Crowd-based Knowledge. EKB Journal Management System, 1(First International Undergraduate Research Conference, IUGRC), 92-92. doi: 10.21608/iugrc.2016.91145
Wu Yiwen; Zhang Yang. "A New Method to Evaluate Bug Severity by using the Crowd-based Knowledge". EKB Journal Management System, 1, First International Undergraduate Research Conference, IUGRC, 2016, 92-92. doi: 10.21608/iugrc.2016.91145
Yiwen, W., Yang, Z. (2016). 'A New Method to Evaluate Bug Severity by using the Crowd-based Knowledge', EKB Journal Management System, 1(First International Undergraduate Research Conference, IUGRC), pp. 92-92. doi: 10.21608/iugrc.2016.91145
Yiwen, W., Yang, Z. A New Method to Evaluate Bug Severity by using the Crowd-based Knowledge. EKB Journal Management System, 2016; 1(First International Undergraduate Research Conference, IUGRC): 92-92. doi: 10.21608/iugrc.2016.91145

A New Method to Evaluate Bug Severity by using the Crowd-based Knowledge

The International Undergraduate Research Conference
Article 10, Volume 1, First International Undergraduate Research Conference, IUGRC, 2016, Page 92-92  XML PDF (422.53 K)
Document Type: Original Article
DOI: 10.21608/iugrc.2016.91145
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Authors
Wu Yiwen1; Zhang Yang2
1National University of Defense Technology, China.
2Computer of School, National University of Defense Technology, China.
Abstract
In bug tracking system, the high volume of incoming bug reports poses a serious challenge to project managers. Triaging these bug reports manually consumes time and resources which leads to delaying the resolution of important bugs. StackOverflow is the most popular crowdsourcing Q&A community with plenty of bug-related posts. In this paper, we propose a new method to evaluate bug severity by exploiting available quantitative crowd-based knowledge from the bug-related posts in StackOverflow. Two typical type of projects’ bug repositories are studied here, e.g. Mozilla and Eclipse. Our study shows that using crowd-based knowledge is able capture the technical merits as well as the programming solutions and it has the potential to optimize the existing evaluation methods of bug severity by incorporating the crowd-based knowledge from a third-party in future.
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