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A mixed-methods analysis of micro-collaborative coding practices in OpenStack
Technical collaboration between multiple contributors is a natural phenomenon in distributed open source software development projects. Macro-collaboration, where each code commit is attributed to a single collaborator, has been extensively studied in the research literature. This is much less the c...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9206143/ https://www.ncbi.nlm.nih.gov/pubmed/35757446 http://dx.doi.org/10.1007/s10664-022-10167-w |
Sumario: | Technical collaboration between multiple contributors is a natural phenomenon in distributed open source software development projects. Macro-collaboration, where each code commit is attributed to a single collaborator, has been extensively studied in the research literature. This is much less the case for so-called micro-collaboration practices, in which multiple authors contribute to the same commit. To support such practices, GitLab and GitHub started supporting social coding mechanisms such as the “Co-Authored-By:” trailers in commit messages, which, in turn, enable to empirically study such micro-collaboration. In order to understand the mechanisms, benefits and limitations of micro-collaboration, this article provides an exemplar case study of collaboration practices in the OpenStack ecosystem. Following a mixed-method research approach we provide qualitative evidence through a thematic and content analysis of semi-structured interviews with 16 OpenStack contributors. We contrast their perception with quantitative evidence gained by statistical analysis of the git commit histories ([Formula: see text] 1M commits) and Gerrit code review histories ([Formula: see text] 631K change sets and [Formula: see text] 2M patch sets) of 1,804 OpenStack project repositories over a 9-year period. Our findings provide novel empirical insights to practitioners to promote micro-collaborative coding practices, and to academics to conduct further research towards understanding and automating the micro-collaboration process. |
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