Software development is a process fraught with unpredictability, in part because software is created by people. Human interactions add complexity to development processes, and collaborative development can become a liability if not properly understood and managed. Recent years have seen an increase in the use of data mining techniques on publicly-available repository data with the goal of improving software development processes, and by extension, software quality. In this thesis, we introduce the concept of author entropy as a metric for quantifying interaction and collaboration (both within individual files and across projects), present results from two empirical observational studies of open-source projects, identify and analyze authorship and collaboration patterns within source code, demonstrate techniques for visualizing authorship patterns, and propose avenues for further research.
Identifer | oai:union.ndltd.org:BGMYU2/oai:scholarsarchive.byu.edu:etd-3970 |
Date | 02 March 2012 |
Creators | Taylor, Quinn Carlson |
Publisher | BYU ScholarsArchive |
Source Sets | Brigham Young University |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Theses and Dissertations |
Rights | http://lib.byu.edu/about/copyright/ |
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