We describe an experience in teaching global software engineering (GSE) using distributed Scrum augmented with industrial best practices. Our unique instructional technique had students work in both same-site and cross-site teams to contrast the two modes of working. The course was a collaboration between Aalto University, Finland and University of Victoria, Canada. Fifteen Canadian and eight Finnish students worked on a single large project, divided into four teams, working on interdependent user stories as negotiated with the industrial product owner located in Finland. Half way through the course, we changed the teams so each student worked in both a local and a distributed team. We studied student learning using a mixed-method approach including 14 post-course interviews, pre-course and Sprint questionnaires, observations, meeting recordings, and repository data from git and Flow dock, the primary communication tool. Our results show no significant differences between working in distributed vs. Non-distributed teams, suggesting that Scrum helps alleviate many GSE problems. Our post-course interviews and survey data allows us to explain this effect, we found that students over time learned to better self-select tasks with less inter-team dependencies, to communicate more, and to work better in teams.

Software projects are not developed in isolation. Recent research has shifted to studying software ecosystems, communities of projects that depend on each other and are developed together. However, identifying technical dependencies at the ecosystem level can be challenging. In this paper, we propose a new method, known as reference coupling, for detecting technical dependencies between projects. The method establishes dependencies through user-specified cross-references between projects. We use our method to identify ecosystems in GitHub-hosted projects, and we identify several characteristics of the identified ecosystems. We find that most ecosystems are centered around one project and are interconnected with other ecosystems. The predominant type of ecosystems are those that develop tools to support software development. We also found that the project owners' social behaviour aligns well with the technical dependencies within the ecosystem, but project contributors' social behaviour does not align with these dependencies. We conclude with a discussion on future research that is enabled by our reference coupling method.