Automated identification of high impact bug reports leveraging imbalanced learning strategies

Automated identification of high impact bug reports leveraging imbalanced learning strategies

In practice, some bugs have more impact than others and thus deserve more immediate attention. Due to tight schedule and limited human resource, developers may not have enough time to inspect all bugs. Thus, they often concentrate on bugs that are highly impactful. In the literature, high impact bug...

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Bibliographic Details
Main Authors: YANG, Xinli, David LO, HUANG, Qiao, XIA, Xin, SUN, Jianling
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2016
Subjects:
High Impact Bug
Imbalanced Data
Text Classification
Computer Sciences
Software Engineering
Online Access:https://ink.library.smu.edu.sg/sis_research/3567
https://ink.library.smu.edu.sg/context/sis_research/article/4568/viewcontent/AutomatedIDHighImpactBugReportsLimbalLearning_2016.pdf
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Institution: Singapore Management University
Language: English

Internet

https://ink.library.smu.edu.sg/sis_research/3567
https://ink.library.smu.edu.sg/context/sis_research/article/4568/viewcontent/AutomatedIDHighImpactBugReportsLimbalLearning_2016.pdf

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