NDLI: Empirical validation of object-oriented metrics on open source software for fault prediction

Content Provider	IEEE Xplore Digital Library
Author	Gyimothy, T. Ferenc, R. Siket, I.
Copyright Year	1976
Abstract	Open source software systems are becoming increasingly important these days. Many companies are investing in open source projects and lots of them are also using such software in their own work. But, because open source software is often developed with a different management style than the industrial ones, the quality and reliability of the code needs to be studied. Hence, the characteristics of the source code of these projects need to be measured to obtain more information about it. This paper describes how we calculated the object-oriented metrics given by Chidamber and Kemerer to illustrate how fault-proneness detection of the source code of the open source Web and e-mail suite called Mozilla can be carried out. We checked the values obtained against the number of bugs found in its bug database - called Bugzilla - using regression and machine learning methods to validate the usefulness of these metrics for fault-proneness prediction. We also compared the metrics of several versions of Mozilla to see how the predicted fault-proneness of the software system changed during its development cycle.
Sponsorship	IEEE Computer Society Technical Council on Software Engineering Association for Computing Machinery (ACM) IEEE Computer Society
Starting Page	897
Ending Page	910
Page Count	14
File Size	1669965
File Format	PDF
ISSN	00985589
Volume Number	31
Issue Number	10
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Open source software Quality management Software development management Computer industry Fault detection Electronic mail Computer bugs Object oriented databases Learning systems Software systems Columbus. Index Terms- Fact extraction metrics validation reverse engineering open source software fault-proneness detection Mozilla Bugzilla C++ compiler wrapping
Content Type	Text
Resource Type	Article
Subject	Software

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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
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