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- W3164578412 abstract "Abstract 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 , a scalable software that facilitates the extraction of fine-grained co-editing networks in large 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 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 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." @default.
- W3164578412 created "2021-06-07" @default.
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- W3164578412 date "2021-05-26" @default.
- W3164578412 modified "2023-10-17" @default.
- W3164578412 title "Analysing Time-Stamped Co-Editing Networks in Software Development Teams using git2net" @default.
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- W3164578412 doi "https://doi.org/10.1007/s10664-020-09928-2" @default.
- W3164578412 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8550015" @default.
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