Developer Cooperation Relationship and Attribute Similarity Based Community Detection in Software Ecosystem  

作　　者：SHEN Xin DU Junwei GONG Dunwei YAO Xiangjuan 

机构地区：[1]School of Information and Control Engineering,China University of Mining and Technology,Xuzhou 221116,China [2]School of Information Science and Technology,Qingdao University of Science and Technology,Qingdao 266061,China [3]School of Mathematics,China University of Mining and Technology,Xuzhou 221116,China

出　　处：《Chinese Journal of Electronics》2023年第1期39-50,共12页电子学报（英文版）

基　　金：supported by the National Key Research and Development Program of China(2018YFB1003802)。

摘　　要：A software ecosystem(SECO)can be described as a special complex network.Previous complex networks in an SECO have limitations in accurately reflecting the similarity between each pair of nodes.The community structure is critical towards understanding the network topology and function.Many scholars tend to adopt evolutionary optimization methods for community detection.The information adopted in previous optimization models for community detection is incomprehensive and cannot be directly applied to the problem of community detection in an SECO.Based on this,a complex network in SECOs is first built.In the network,the cooperation intensity between developers is accurately calculated,and the attribute contained by each developer is considered.A multi-objective optimization model is formulated.A community detection algorithm based on NSGA-II is employed to solve the above model.Experimental results demonstrate that the proposed method of calculating the developer cooperation intensity and our model are advantageous.

关 键 词：Software ecosystem Complex network Cooperation intensity Attribute similarity Community detection 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]