ISCAS OpenIR
an empirical study on identifying core developers using network analysis
Zhang Wen; Yang Ye; Wang Qing
2012
Conference Name2nd International Workshop on Evidential Assessment of Software Technologies, EAST 2012
SourceEAST'12 - Proceedings of the 2nd International Workshop on Evidential Assessment of Software Technologies
Pages43-48
Conference DateSeptember 22, 2012 - September 22, 2012
Conference PlaceLund, Sweden
Indexed TypeEI
ISBN9781450315098
Department(1) Laboratory for Internet Software Technologies Institute of Software Chinese Academy of Sciences Beijing 100190 China
English AbstractThis paper conducts an empirical study of ArgoUML project to identify its core developers of each release. Unlike most previous studies regarding OSS email archives as a whole social network,our focus is on the quantitative analysis of a series of social networks produced in the process of OSS evolution. We attempt two types of networks as unipartite network and bipartite network. With unipartite network, we construct the network using developer cooperation information. With bipartite network, we construct the network using both developer information and email topic information. Experimental results demonstrate that bipartite network has produced better results in core developer identification than traditional unipartite network. Moreover, degree is more effective in identifying core developers from networks than other measures. We present the explanation for the experimental outcome. Copyright 2012 ACM.; This paper conducts an empirical study of ArgoUML project to identify its core developers of each release. Unlike most previous studies regarding OSS email archives as a whole social network,our focus is on the quantitative analysis of a series of social networks produced in the process of OSS evolution. We attempt two types of networks as unipartite network and bipartite network. With unipartite network, we construct the network using developer cooperation information. With bipartite network, we construct the network using both developer information and email topic information. Experimental results demonstrate that bipartite network has produced better results in core developer identification than traditional unipartite network. Moreover, degree is more effective in identifying core developers from networks than other measures. We present the explanation for the experimental outcome. Copyright 2012 ACM.
KeywordSocial Networking (Online)
SponsorshipACM Special Interest Group on Software Engineering (SIGSOFT); IEEE Computer Society (CS)
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/15893
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
Zhang Wen,Yang Ye,Wang Qing. an empirical study on identifying core developers using network analysis[C],2012:43-48.
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