Software

Predicting Software Build Failure Using Source Code Metrics

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Executive Summary

In this paper, the authors describe the extraction of source code metrics from the Jazz repository and the application of data mining techniques to identify the most useful of those metrics for predicting the success or failure of an attempt to construct a working instance of the software product. They present results from a study using the J48 classification method used in conjunction with a number of attribute selection strategies applied to a set of source code metrics calculated from the code base at the beginning of a build cycle. The results indicate that only a relatively small number of the available software metrics that they considered have any significance for predicting the outcome of a build.

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