The distribution of faults in a large industrial software system
ISSTA '02 Proceedings of the 2002 ACM SIGSOFT international symposium on Software testing and analysis
Predicting the Location and Number of Faults in Large Software Systems
IEEE Transactions on Software Engineering
Comparing the effectiveness of several modeling methods for fault prediction
Empirical Software Engineering
Does measuring code change improve fault prediction?
Proceedings of the 7th International Conference on Predictive Models in Software Engineering
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In earlier studies of multiple-release systems, we observed that the number of changes and the number of faults in a file in the past release, the size of a file, and the maturity of a file are all useful predictors of the file's fault proneness in the next release. In each case the data needed to make predictions have been extracted from a configuration management system which provides integrated change management and version control functionality. In this paper we investigate analogous questions for the system as a whole, rather than looking at its constituent files. Using two large industrial software systems, each with many field releases, we examine a number of questions relating defects to system maturity, how often the system has changed, the size difference of a release from the prior release, and the length of time a release has been under development before the start of system testing. Most of our observations match neither our intuition, nor the relations observed for these two systems when similar questions were asked at the file level.