First International Symposium on Empirical Software Engineering and Measurement (ESEM 2007) Generalizing fault contents from a few classes Madrid, Spain September 20-September 21 ISBN: 0-7695-2886-4
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ESEM.2007.39
The challenges in fault prediction today are to get a prediction as early as possible, at as low a cost as possible, needing as little data as possible and preferably in such a language that your average developer can understand where it came from. This paper presents a fault sampling method where a summary of a few, easily available metrics is used together with the results of a few sampled classes to generalize the fault content to an entire system. The method is tested on a large software system written in Java, that currently consists of around 2 000 classes and 300 000 lines of code. The evaluation shows that the fault generalization method is good at predicting fault-prone clusters and that it is possible to generalize the values of a few representative classes.
Citation:
Hanna Scott, Philip M. Johnson, "Generalizing fault contents from a few classes," esem, pp.205-214, First International Symposium on Empirical Software Engineering and Measurement (ESEM 2007), 2007 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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