The Ubuntu Linux Distribution represents a massive investment of time and human effort to produce a reliable computing experience for users. To accomplish these goals, software bugs must be tracked and fixed. However, as the number of users increase and bug reports grow advanced tools such as data mining must be used to increase the effectiveness of all contributors to the project. Thus, this report involved collecting a large amount of bug reports into a database and calculating relevant statistics. Because of the diversity and quantity of bug reports, contributors must find which bugs are most relevant and important to work on. One study in this report created an automatic way to determine who is best fit to solve a particular bug by using classification techniques. In addition, this report explores how to initially classify if a bug report will be eventually marked invalid or not. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2012-08-6196 |
| Date | 27 November 2012 |
| Creators | Arges, Christopher John |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | thesis |
| Format | application/pdf |
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