Mining developer communication streams
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Academy & Industry Research Collaboration Center (AIRCC) Publishing Corporation
Abstract
This paper explores the concepts of modelling a software development project as a process that results in the creation of a continuous stream of data. In terms of the Jazz repository used in this research, one aspect of that stream of data would be developer communication. Such data can be used to create an evolving social network characterized by a range of metrics. This paper presents the application of data stream mining techniques to identify the most useful metrics for predicting build outcomes. Results are presented from applying the Hoeffding Tree classification method used in conjunction with the Adaptive Sliding Window (ADWIN) method for detecting concept drift. The results indicate that only a small number of the available metrics considered have any significance for predicting the outcome of a build.Description
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Fourth International Conference on Computer Science & Information Technology held at Pullman Hotel, Sydney, 2014-02-21 to 2014-02-22, published in: CS & IT-CSCP 2014, pp.13 - 25
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Computer Science & Information Technology (CS & IT) is an open access-Computer Science Conference Proceedings (CSCP) series that welcomes conferences to publish their proceedings / post conference proceedings.