{"title":"Degree doesn't Matter: Identifying the Drivers of Interaction in Software Development Ecosystems","authors":"I. Bardhan, Subhajit Datta, S. Majumder","doi":"10.1109/APSEC53868.2021.00048","DOIUrl":null,"url":null,"abstract":"Large scale software development ecosystems represent one of the most complex human enterprises. In such settings, developers are embedded in a web of shared concerns, responsibilities, and objectives at individual and collective levels. A deep understanding of the factors that influence developers to connect with one another is crucial in appreciating the challenges of such ecosystems as well as formulating strategies to overcome those challenges. We use real world data from multiple software development ecosystems to construct developer interaction networks and examine the mechanisms of such network formation using statistical models to identify developer attributes that have maximal influence on whether and how developers connect with one another. Our results challenge the conventional wisdom on the importance of particular developer attributes in their interaction practices, and offer useful insights for individual developers, project managers, and organizational decision-makers.","PeriodicalId":143800,"journal":{"name":"2021 28th Asia-Pacific Software Engineering Conference (APSEC)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 28th Asia-Pacific Software Engineering Conference (APSEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSEC53868.2021.00048","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
Large scale software development ecosystems represent one of the most complex human enterprises. In such settings, developers are embedded in a web of shared concerns, responsibilities, and objectives at individual and collective levels. A deep understanding of the factors that influence developers to connect with one another is crucial in appreciating the challenges of such ecosystems as well as formulating strategies to overcome those challenges. We use real world data from multiple software development ecosystems to construct developer interaction networks and examine the mechanisms of such network formation using statistical models to identify developer attributes that have maximal influence on whether and how developers connect with one another. Our results challenge the conventional wisdom on the importance of particular developer attributes in their interaction practices, and offer useful insights for individual developers, project managers, and organizational decision-makers.