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PhD Final Examination – Amirhosein Azarbakht


Thursday, May 18, 2017 8:00 AM - 10:00 AM

Longitudinal Analysis of Collaboration in Forked Open Source Software Development Projects
Social interactions are a ubiquitous part of our lives, and the creation of online social communities has been a natural extension of this phenomena. Free and Open Source Software (FOSS) development efforts are prime examples of how communities can be leveraged in software development, where groups are formed around communities of interest, and depend on continued interest and involvement. Not everything works smoothly all the time in open source projects. Problems arise for a variety of reasons, including collaboration and communication problems, which results in uncertainty about the operational health and survivability of the projects. Many stake-holders are affected by this uncertainty, including industry sponsors, individual contributors, corporate developers, and users, who all have decided to invest time and effort in the project, and will be affected if a project suffers from troubles. Forking in FOSS, either as a non-friendly split or a friendly divide, affects the community. Such effects have been studied, shedding light on how forking happens. However, most existing research on forking is post-hoc. In this study, we focus on the seldom-studied run-up to forking events. We used the following two approaches to study the evolution and social dynamics of FOSS communities; 1) Time series analysis of the contents of the messages sent and received on the projects developers mailing list, for the time period of 10-month run-up to the fork was analyzed for anomalies, indicative of simmering conflicts. 2) Social network analysis using a developer-oriented approach to statistically model the changes a community goes through in the run-up to a fork, in which the model represents tie formation, tie breakage, and tie maintenance between developers. We estimated several model parameters that capture the variance in the changes the community goes through. We found that conflict-driven forks exhibited anomalies; time series analysis of sentiments showed the anomalies occurred before and close to the fork event. Whereas non-conflict-driven forks did not suffer from such pre-fork anomalies.

Major Advisor: Carlos Jensen
Committee: Ron Metoyer
Committee: Cindy Grimm
Committee: Drew Gerkey
GCR: Yelda Turkan


Kelley Engineering Center (campus map)
1005
Calvin Hughes
1 541 737 3168
Calvin.Hughes at oregonstate.edu
Sch Elect Engr/Comp Sci
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