{"title":"Early Identification of Active Developers Based on their Past Contributions in OSS Projects","authors":"Tomoki Koguchi, Akinori Ihara","doi":"10.1109/SNPD51163.2021.9704917","DOIUrl":null,"url":null,"abstract":"Open Source Software (OSS) developers are free to contribute and free to leave a project, if the project is (not) suitable for them. On the one hand, OSS projects need to manage the human resource to continuously maintain OSS in the future. Some existing studies proposed an approach that estimates how long developers contribute to OSS projects. Using developers’ contributions during the first few months in the target project, the proposed model identified long-term contributors or core developers. However, the approach frequently miss to find capable developers because many developers leave the project soon after participating. To avoid the loss of capable developers, this study build a prediction model to identify future active developers based on their past contributions to any OSS projects. Using dataset from four large-scale OSS projects as a case study, we evaluated our proposed model to identify future active developers based on their past contributions to any OSS projects before participating in a future target project. Our proposed approach contributes to manage human resource in OSS development process.","PeriodicalId":235370,"journal":{"name":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE/ACIS 22nd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SNPD51163.2021.9704917","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Open Source Software (OSS) developers are free to contribute and free to leave a project, if the project is (not) suitable for them. On the one hand, OSS projects need to manage the human resource to continuously maintain OSS in the future. Some existing studies proposed an approach that estimates how long developers contribute to OSS projects. Using developers’ contributions during the first few months in the target project, the proposed model identified long-term contributors or core developers. However, the approach frequently miss to find capable developers because many developers leave the project soon after participating. To avoid the loss of capable developers, this study build a prediction model to identify future active developers based on their past contributions to any OSS projects. Using dataset from four large-scale OSS projects as a case study, we evaluated our proposed model to identify future active developers based on their past contributions to any OSS projects before participating in a future target project. Our proposed approach contributes to manage human resource in OSS development process.