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Mining Eclipse Developer Contributions via Author-Topic Models

, , , , and . Proceedings of the Fourth International Workshop on Mining Software Repositories, page 30. IEEE Computer Society, (2007)

Abstract

We present the results of applying statistical author-topic models to a subset of the Eclipse 3.0 source code consisting of 2,119 source files and 700,000 lines of code from 59 developers. This technique provides an intuitive and automated framework with which to mine developer contributions and competencies from a given code base while simultaneously extracting software function in the form of topics. In addition to serving as a convenient summary for program function and developer activities, our study shows that topic models provide a meaningful, effective, and statistical basis for developer similarity analysis.

Description

based on the eclipse dataset the author-topic is applied The goal of this paper is to identify the developer who will contribute to a bug most likely

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