Analysing Time-Stamped Co-Editing Networks in Software Development Teams using git2net

Data from software repositories have become an important foundation for the empirical study of software engineering processes. A recurring theme in the repository mining literature is the inference of developer networks capturing e.g. collaboration, coordination, or communication from the commit history of projects. Many works in this area studied networks of co-authorship of software artefacts, neglecting detailed information on code changes and code ownership available in software repositories. To address this issue, we introduce git2net, a scalable python software that facilitates the extraction of fine-grained co-editing networks in large git repositories. It uses text mining techniques to analyse the detailed history of textual modifications within files. We apply our tool in two case studies using GitHub repositories of multiple Open Source as well as a proprietary software project. Specifically, we use data on more than 1.2 million commits and more than 25,000 developers to test a hypothesis on the relation between developer productivity and co-editing patterns in software teams. We argue that git2net opens up an important new source of high-resolution data on human collaboration patterns that can be used to advance theory in empirical software engineering, computational social science, and organisational studies.

Automated summary

Data from software repositories is crucial for studying software engineering processes. Git2net is a scalable Python software that extracts fine-grained co-editing networks from large git repositories, allowing researchers to analyze developer collaboration patterns. By applying the tool to two case studies with data from over 1.2 million commits and more than 25,000 developers, a hypothesis on the relationship between developer productivity and co-editing patterns in software teams was tested. Git2net provides high-resolution data on human collaboration patterns for advancing theories in empirical software engineering, computational social science, and organizational studies.