Open source projects are often supported by companies. Such involvement affects the robust contributor inflow needed to sustain the project and sometimes prompts key contributors to leave. To capture user innovation and to maintain quality of software and productivity of teams these projects need to attract and retain contributors. We try to understand and quantify how inflow and retention are shaped by policies and actions of companies in three application server projects. We identify three hybrid projects implementing the same JavaEE specification and use published literature, online materials, and interviews to quantify actions and policies companies used to get involved. We collect project repository data, analyze affiliation history of project participants, and use generalized linear models and survival analysis to measure contributor inflow and retention. We found that full control mechanisms and high intensity of commercial involvement were associated with a decrease of external inflow and with improved retention. However, a shared control mechanism was associated with increased external inflow contemporaneously with the increase of commercial involvement. The methods enable us to quantify aspects of the balance between community and private interests in open source software projects and provide clear implications to inform the structure of future open source communities.

Prof. Minghui Zhou focuses on using the data recorded in vast open source and commercial software repositories to investigate how people develop software and how they interact with each other to accomplish their tasks. Her research subjects range from the fluency and learning trajectory of developers to the micro-practices of projects, and to the health and sustainability of communities and ecosystems. She published more than 40 referred papers in journals and international conferences including TSE, TOSEM, ICSE and FSE. She received ACM SIGSOFT (FSE 2010) Distinguished paper award. She served as PC in various conferences, such as FSE 2014 Tool Demo Track (PC Co-Chair), MSR 2016 and ICSE 2018. She consults for several companies regarding software metrics and inner source.

Cognitive scientists tell us that we are hardwired for deceptionoverly optimistic about outcomes. In fact, we surely wouldnt have survived without this trait. With this built-in bias as a starting point, its no wonder that software managers and teams almost always develop poor estimates. But that doesnt mean all is lost. We must simply accept that our estimates are optimistic guesses and continually re-evaluate as we go. Linda Rising has been part of many development projects where sincere, honest people wanted to make the best estimates possible and used scientific approaches to make it happenand all for naught. In many projects, because re-estimation was regarded as an admission of failure, the team spent too much time and endless meetings trying to get it right. Offering examples from ordinary lifeespecially from the way people eat and drinkLinda demonstrates how hard it is for us to see our poor estimating skills and offers practical advice on living and working with the self-deception that is hardwired in all of us.