Developer Role Evolution in Open Source Software Ecosystem： An Explanatory Study on GNOME  

作　　者：Can Cheng Bing Li Zeng-Yang Li Yu-Qi Zhao Feng-Ling Liao 

机构地区：[1]International School of Software, Wuhan University, Wuhan 430072, China [2]State Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, China [3]Complex Networks Research Center, Wuhan University, Wuhan 430072, China

出　　处：《Journal of Computer Science & Technology》2017年第2期396-414,共19页计算机科学技术学报（英文版）

基　　金：This work is supported by the National Key Research and Development Program of China under Grant No. 2016YFB0800400, the National Basic Research 973 Program of China under Grant No. 2014CB340404, the National Natural Science Foundation of China under Grant Nos. 61572371, 61273216, and 61272111, the China Postdoctoral Science Foundation （CPSF） under Grant No. 2015M582272, the Natural Science Foundation of Hubei Province of China under Grant No. 2016CFB158, and the Fundamental Research Funds for the Central Universities of China under Grant No. 2042016kf0033.

摘　　要：An open source software （OSS） ecosystem refers to an OSS development community composed of many software projects and developers contributing to these projects. The projects and developers co-evolve in an ecosystem. To keep healthy evolution of such OSS ecosystems, there is a need of attracting and retaining developers, particularly project leaders and core developers who have major impact on the project and the whole team. Therefore, it is important to figure out the factors that influence developers＇ chance to evolve into project leaders and core developers. To identify such factors, we conducted a case study on the GNOME ecosystem. First, we collected indicators reflecting developers＇ subjective willingness to contribute to the project and the project environment that they stay in. Second, we calculated such indicators based on the GNOME dataset. Then, we fitted logistic regression models by taking as independent variables the resulting indicators after eliminating the most collinear ones, and taking as a dependent variable the future developer role （the core developer or project leader）. The results showed that part of such indicators （e.g., the total number of projects that a developer joined） of subjective willingness and project environment significantly influenced the developers＇ chance to evolve into core developers and project leaders. With different validation methods, our obtained model performs well on predicting developmental core developers, resulting in stable prediction performance （0.770, F-value）.An open source software （OSS） ecosystem refers to an OSS development community composed of many software projects and developers contributing to these projects. The projects and developers co-evolve in an ecosystem. To keep healthy evolution of such OSS ecosystems, there is a need of attracting and retaining developers, particularly project leaders and core developers who have major impact on the project and the whole team. Therefore, it is important to figure out the factors that influence developers＇ chance to evolve into project leaders and core developers. To identify such factors, we conducted a case study on the GNOME ecosystem. First, we collected indicators reflecting developers＇ subjective willingness to contribute to the project and the project environment that they stay in. Second, we calculated such indicators based on the GNOME dataset. Then, we fitted logistic regression models by taking as independent variables the resulting indicators after eliminating the most collinear ones, and taking as a dependent variable the future developer role （the core developer or project leader）. The results showed that part of such indicators （e.g., the total number of projects that a developer joined） of subjective willingness and project environment significantly influenced the developers＇ chance to evolve into core developers and project leaders. With different validation methods, our obtained model performs well on predicting developmental core developers, resulting in stable prediction performance （0.770, F-value）.

关 键 词：developer role evolution open source software ecosystem project environment subjective willingness 

分 类 号：TP[自动化与计算机技术]