Revisiting Aristotle vs. Ringelmann: The influence of biases on measuring productivity in Open Source software development
August 08, 2024 Β· Declared Dead Β· π Brazilian Symposium on Software Engineering
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Authors
Christian Gut, Alfredo Goldman
arXiv ID
2408.04782
Category
cs.SE: Software Engineering
Citations
0
Venue
Brazilian Symposium on Software Engineering
Last Checked
5 months ago
Abstract
Aristotle vs. Ringelmann was a discussion between two distinct research teams from the ETH ZΓΌrich who argued whether the productivity of Open Source software projects scales sublinear or superlinear with regard to its team size. This discussion evolved around two publications, which apparently used similar techniques by sampling projects on GitHub and running regression analyses to answer the question about superlinearity. Despite the similarity in their research methods, one team around Ingo Scholtes reached the conclusion that projects scale sublinear, while the other team around Didier Sornette ascertained a superlinear relationship between team size and productivity. In subsequent publications, the two authors argue that the opposite conclusions may be attributed to differences in project populations, since 81.7% of Sornette's projects have less than 50 contributors. Scholtes, on the other hand, sampled specifically projects with more than 50 contributors. This publication compares the research from both authors by replicating their findings, thus allowing for an evaluation of how much project sampling actually accounted for the differences between Scholtes' and Sornette's results. Thereby, the discovery was made that sampling bias only partially explains the discrepancies between the two authors. Further analysis led to the detection of instrumentation biases that drove the regression coefficients in opposite directions. These findings were then consolidated into a quantitative analysis, indicating that instrumentation biases contributed more to the differences between Scholtes' and Sornette's work than the selection bias suggested by both authors.
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