NDLI: Bug prediction based on fine-grained module histories

Content Provider	IEEE Xplore Digital Library
Author	Hata, H. Mizuno, O. Kikuno, T.
Copyright Year	2012
Description	Author affiliation: Osaka University, Osaka, Japan (Hata, H.; Kikuno, T.) \|\| Kyoto Institute of Technology, Kyoto, Japan (Mizuno, O.)
Abstract	There have been many bug prediction models built with historical metrics, which are mined from version histories of software modules. Many studies have reported the effectiveness of these historical metrics. For prediction levels, most studies have targeted package and file levels. Prediction on a fine-grained level, which represents the method level, is required because there may be interesting results compared to coarse-grained (package and file levels) prediction. These results include good performance when considering quality assurance efforts, and new findings about the correlations between bugs and histories. However, fine-grained prediction has been a challenge because obtaining method histories from existing version control systems is a difficult problem. To tackle this problem, we have developed a fine-grained version control system for Java, Historage. With this system, we target Java software and conduct fine-grained prediction with well-known historical metrics. The results indicate that fine-grained (method-level) prediction outperforms coarse-grained (package and file levels) prediction when taking the efforts necessary to find bugs into account. Using a correlation analysis, we show that past bug information does not contribute to method-level bug prediction.
Starting Page	200
Ending Page	210
File Size	402320
Page Count	11
File Format	PDF
ISBN	9781467310666
ISSN	02705257
e-ISBN	9781467310673
e-ISBN	9781467310659
DOI	10.1109/ICSE.2012.6227193
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-02
Publisher Place	Switzerland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement History Predictive models Computer bugs Software Java Complexity theory effort-based evaluation bug prediction fine-grained prediction finegrained histories historical metrics
Content Type	Text
Resource Type	Article
Subject	Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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