DocumentCode :
2272261
Title :
An empirical study on bug assignment automation using Chinese bug data
Author :
Lin, Zhongpeng ; Shu, Fengdi ; Yang, Ye ; Hu, Chenyong ; Wang, Qing
Author_Institution :
Inst. of Software, Chinese Acad. of Sci., Beijing, China
fYear :
2009
fDate :
15-16 Oct. 2009
Firstpage :
451
Lastpage :
455
Abstract :
Bug assignment is an important step in bug life-cycle management. In large projects, this task would consume a substantial amount of human effort. To compare with the previous studies on automatic bug assignment in FOSS (free/open source software) projects, we conduct a case study on a proprietary software project in China. Our study consists of two experiments of automatic bug assignment, using Chinese text and the other non-text information of bug data respectively. Based on text data of the bug repository, the first experiment uses SVM to predict bug assignments and achieve accuracy close to that by human triagers. The second one explores the usefulness of non-text data in making such prediction. The main results from our study includes that text data are most useful data in the bug tracking system to triage bugs, and automation based on text data could effectively reduce the manual effort.
Keywords :
program debugging; public domain software; software maintenance; statistical analysis; support vector machines; text analysis; Chinese bug textual data; FOSS; SVM; automatic bug assignment; bug life-cycle management; bug repository; empirical study; free/open source software project; triage bug tracking system; Automation; Computer bugs; Data mining; Engineering management; Humans; Open source software; Software debugging; Software engineering; Software measurement; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Empirical Software Engineering and Measurement, 2009. ESEM 2009. 3rd International Symposium on
Conference_Location :
Lake Buena Vista, FL
ISSN :
1938-6451
Print_ISBN :
978-1-4244-4842-5
Electronic_ISBN :
1938-6451
Type :
conf
DOI :
10.1109/ESEM.2009.5315994
Filename :
5315994
Link To Document :
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