Mining Software Metrics From the Jazz Repository

This paper describes the extraction of source code metrics from the Jazz repository and the systematic 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. Results are presented 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. These strategies involve the investigation of differing slices of code from the version control system and the cross-dataset classification of the various significant metrics in an attempt to work around the multi-collinearity implicit in the available data.

Provided by: ARPN Journal of Systems and Software Topic: Software Date Added: Aug 2011 Format: PDF

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