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

• Published in: IEEE transactions on software engineering Vol. 31; no. 10; pp. 897 - 910
• Main Authors: Gyimothy, T., Ferenc, R., Siket, I.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-10-2005; IEEE Computer Society
• Subjects: Bugzilla; C plus plus; C++; Columbus; compiler wrapping; Computer bugs; Computer industry; Computer programs; Debugging; Electronic mail; Fault detection; fault-proneness detection; Freeware; Hypotheses; Index Terms- Fact extraction; Learning systems; Machine learning; metrics validation; Mozilla; Object oriented; Object oriented databases; Object oriented programming; Open source software; Public domain; Quality management; Regression; Reverse engineering; Software; Software development management; Software engineering; Software systems; Source code; Statistical methods
• ISSN: 0098-5589; 1939-3520
• DOI: 10.1109/TSE.2005.112

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.