Big Data = Big Insights? Operationalising Brooks' Law in a Massive GitHub Data Set

Christoph Gote, Pavlin Mavrodiev, Frank Schweitzer, Ingo Scholtes

Abstract

Massive data from software repositories and collaboration tools are widely used to study social aspects in software development. One question that several recent works have addressed is how a software project's size and structure influence team productivity, a question famously considered in Brooks' law. Recent studies using massive repository data suggest that developers in larger teams tend to be less productive than smaller teams. Despite using similar methods and data, other studies argue for a positive linear or even super-linear relationship between team size and productivity, thus contesting the view of software economics that software projects are diseconomies of scale.

BibTeX

@inproceedings{Gote-al:ICSE22,
  author    = {Christoph Gote and
               Pavlin Mavrodiev and
               Frank Schweitzer and
               Ingo Scholtes},
  title     = {Big Data = Big Insights? Operationalising Brooks' Law in a Massive {GitHub} Data Set},
  booktitle = {ICSE},
  pages     = {262--273},
  publisher = {{ACM}},
  year      = {2022},
}

Big Data = Big Insights? Operationalising Brooks' Law in a Massive GitHub Data Set

Abstract

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