NDLI: Enhancing Defect Prediction with Static Defect Analysis

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Enhancing Defect Prediction with Static Defect Analysis

Content Provider	ACM Digital Library
Author	Hao, Dan Zhang, Lu Tang, Hao Lan, Tian
Abstract	In the software development process, how to develop better software at lower cost has been a major issue of concern. One way that helps is to find more defects as early as possible, on which defect prediction can provide effective guidance. The most popular defect prediction technique is to build defect prediction models based on machine learning. To improve the performance of defect prediction model, selecting appropriate features is critical. On the other hand, static analysis is usually used in defect detection. As static defect analyzers detects defects by matching some well-defined "defect patterns", its result is useful for locating defects. However, defect prediction and static defect analysis are supposed to be two parallel areas due to the differences in research motivation, solution and granularity. In this paper, we present a possible approach to improve the performance of defect prediction with the help of static analysis techniques. Specifically, we present to extract features based on defect patterns from static defect analyzers to improve the performance of defect prediction models. Based on this approach, we implemented a defect prediction tool and set up experiments to measure the effect of the features.
Starting Page	43
Ending Page	51
Page Count	9
File Format	PDF
ISBN	9781450336413
DOI	10.1145/2875913.2875922
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-11-06
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Defect pattern Machine learning Predictive model Static defect analyzer Defect Code feature
Content Type	Text
Resource Type	Article

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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