Who Will Stay in the FLOSS Community? Modeling Participant&apos;s Initial   Behavior

doi:10.1109/TSE.2014.2349496

CORC > 北京大学 > 信息科学技术学院

	Who Will Stay in the FLOSS Community? Modeling Participant's Initial Behavior
	Zhou, Minghui ; Mockus, Audris
刊名	ieee transactions on software engineering
	2015
关键词	Long term contributor open source software issue tracking system mining software repository extent of involvement interaction with environment initial behavior OPEN SOURCE SOFTWARE PERSON-ORGANIZATION FIT DEVELOPMENT TEAMS PERFORMANCE DEVELOPERS WORK METAANALYSIS MOTIVATION GOVERNANCE INNOVATION
DOI	10.1109/TSE.2014.2349496
英文摘要	Motivation: To survive and succeed, FLOSS projects need contributors able to accomplish critical project tasks. However, such tasks require extensive project experience of long term contributors (LTCs). Aim: We measure, understand, and predict how the newcomers' involvement and environment in the issue tracking system (ITS) affect their odds of becoming an LTC. Method: ITS data of Mozilla and Gnome, literature, interviews, and online documents were used to design measures of involvement and environment. A logistic regression model was used to explain and predict contributor's odds of becoming an LTC. We also reproduced the results on new data provided by Mozilla. Results: We constructed nine measures of involvement and environment based on events recorded in an ITS. Macro-climate is the overall project environment while micro-climate is person-specific and varies among the participants. Newcomers who are able to get at least one issue reported in the first month to be fixed, doubled their odds of becoming an LTC. The macro-climate with high project popularity and the micro-climate with low attention from peers reduced the odds. The precision of LTC prediction was 38 times higher than for a random predictor. We were able to reproduce the results with new Mozilla data without losing the significance or predictive power of the previously published model. We encountered unexpected changes in some attributes and suggest ways to make analysis of ITS data more reproducible. Conclusions: The findings suggest the importance of initial behaviors and experiences of new participants and outline empirically-based approaches to help the communities with the recruitment of contributors for long-term participation and to help the participants contribute more effectively. To facilitate the reproduction of the study and of the proposed measures in other contexts, we provide the data we retrieved and the scripts we wrote at https://www.passion-lab.org/projects/developerfluency.html.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000347788400006&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Computer Science, Software Engineering; Engineering, Electrical & Electronic; SCI(E); EI; 1; ARTICLE; zhmh@pku.edu.cn; audris@utk.edu; 1; 82-99; 41
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/151935]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Zhou, Minghui,Mockus, Audris. Who Will Stay in the FLOSS Community? Modeling Participant's Initial Behavior[J]. ieee transactions on software engineering,2015.
APA	Zhou, Minghui,&Mockus, Audris.(2015).Who Will Stay in the FLOSS Community? Modeling Participant's Initial Behavior.ieee transactions on software engineering.
MLA	Zhou, Minghui,et al."Who Will Stay in the FLOSS Community? Modeling Participant's Initial Behavior".ieee transactions on software engineering (2015).