HSPM:A Better Model to Effectively Preventing Open-Source Projects from Dying  

作　　者：Zhifang Liao Fangying Fu Yiqi Zhao Sui Tan Zhiwu Yu Yan Zhang 

机构地区：[1]School of Computer Science and Engineering,Central South University,Changsha,410075,China [2]National Engineering Research Center of High-speed Railway Construction Technology,Changsha,410075,China [3]School of Civil Engineering,Central South University,Changsha,410075,China [4]School of Engineering and Built Environment,Glasgow Caledonian University,Glasgow,G4 OBA,UK

出　　处：《Computer Systems Science & Engineering》2023年第10期431-452,共22页计算机系统科学与工程（英文）

基　　金：This work was supported by the National Social Science Foundation(NSSF)Research on intelligent recommendation of multi-modal resources for children’s graded reading in smart library(22BTQ033);the Science and Technology Research and Development Program Project of China railway group limited(Project No.2021-Special-08).

摘　　要：With the rapid development of Open-Source(OS),more and more software projects are maintained and developed in the form of OS.These Open-Source projects depend on and influence each other,gradually forming a huge OS project network,namely an Open-Source Software ECOsystem(OSSECO).Unfortunately,not all OS projects in the open-source ecosystem can be healthy and stable in the long term,and more projects will go from active to inactive and gradually die.In a tightly connected ecosystem,the death of one project can potentially cause the collapse of the entire ecosystem network.How can we effectively prevent such situations from happening?In this paper,we first identify the basic project characteristics that affect the survival of OS projects at both project and ecosystem levels through the proportional hazards model.Then,we utilize graph convolutional networks based on the ecosystem network to extract the ecosystem environment characteristics of OS projects.Finally,we fuse basic project characteristics and environmental project characteristics and construct a Hybrid Structured Prediction Model(HSPM)to predict the OS project survival state.The experimental results show that HSPM significantly improved compared to the traditional prediction model.Our work can substantially assist OS project managers in maintaining their projects’health.It can also provide an essential reference for developers when choosing the right open-source project for their production activities.

关 键 词：Project survival prediction open-source ecosystem open-source project open-source health graph neural networks 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]