NDLI: AODE for Source Code Metrics for Improved Software Maintainability

Content Provider	IEEE Xplore Digital Library
Author	Yingjie Tian Chuanliang Chen Chunhua Zhang
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Sci., Beijing Normal Univ., Beijing, China (Chuanliang Chen) \|\| Sch. of Inf., Renmin Univ. of China, Beijing, China (Chunhua Zhang) \|\| Res. Centre on Fictitious Econ. & Data Sci., Chinese Acad. of Sci., Beijing, China (Yingjie Tian)
Abstract	Software metrics are collected at various phases of the whole software development process, in order to assist in monitoring and controlling the software quality. However, software quality control is complicated, because of the complex relationship between these metrics and the attributes of a software development process. To solve this problem, many excellent techniques have been introduced into software maintainability domain. In this paper, we propose a novel classification method--Aggregating One-Dependence Estimators (AODE) to support and enhance our understanding of software metrics and their relationship to software quality. Experiments show that performance of AODE is much better than eight traditional classification methods and it is a promising method for software quality prediction. Furthermore, we present a Symmetrical Uncertainty (SU) based feature selection method to reduce source code metrics taking part in classification, make these classifiers more efficient and keep their performances not undermined meanwhile. Our empirical study shows the promising capability of SU for selecting relevant metrics and preserving original performances of the classifiers.
Starting Page	330
Ending Page	335
File Size	482987
Page Count	6
File Format	PDF
ISBN	9780769534015
DOI	10.1109/SKG.2008.43
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-03
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Software maintenance Uncertainty Programming Software Maintainability Support vector machines Computer science Software metrics Source Code Metrics Support vector machine classification Software quality Symmetrical Uncertainty Capability maturity model Bayesian Classifier Quality management
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