Nowadays, successful cooperation and collaboration among developers is crucial to build
successful projects in distributed software system development (DSSD). Assigning wrong
developers to a specific task not only affects the performance of a component of this task but
also affects other components since these projects are composed of dependent components.
Another aspect that should be considered when teams are built is the social relationships between
the members; disagreements between these members also affect the project team’s performance.
These two aspects might cause a project’s failure or delay. Therefore, they are important to
consider when teams are created. In this thesis, we developed an Expert Recommender System
Framework (ERSF) that assists developers (Active Developers) to find experts who can help
them complete or fix the bugs in the code at hand. The ERSF analyzes the developer technical
expertise on similar code fragments to the one they need help on assuming that those who have
worked on similar fragments might understand and help the Active Developer; also, it analyzes
their social relationships with the Active Developer as well as their social activities within the
DSSD. Our work is also concerned with improving the system performance and
recommendations by tracking the developer communications through our ERSF in order to keep
developer profiles up-to-date. Technical expertise and sociality are measured using a
combination of technical and social heuristics. The recommender system was tested using
scenarios derived from real software development data, and its recommendations compared
favourably to recommendations that humans were asked to make in the same scenarios; also,
they were compared to the recommendations of the NaiveBayes and other machine learning
algorithms. Our experiment results show that ERSF can recommend experts with good to
excellent accuracy.
| Identifer | oai:union.ndltd.org:USASK/oai:ecommons.usask.ca:10388/ETD-2013-07-1116 |
| Date | 2013 July 1900 |
| Contributors | McCalla, Dr. Gord, Roy, Dr. Chanchal |
| Source Sets | University of Saskatchewan Library |
| Language | English |
| Detected Language | English |
| Type | text, thesis |
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