Reference

Citations

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Meyer2017

André N. Meyer, Laura E. Barton, Gail C. Murphy, Thomas Zimmermann, and Thomas Fritz: “The Work Life of Developers: Activities, Switches and Perceived Productivity.” IEEE Trans. Software Engineering, 43(12), 2017, 10.1109/tse.2017.2656886.
Monitoring 20 developers over 11 work-days shows more user input correlates with higher perceived productivity; emails and planned meetings correlate negatively; productivity is highly personal and varies by time of day.

Nielsen1993

Jakob Nielsen and Thomas K. Landauer: “A Mathematical Model of the Finding of Usability Problems.” Proc. INTERACT’93 and CHI’93, 206-213, 1993, 10.1145/169059.169166.
Develops a mathematical model showing that approximately five participants are sufficient to identify most major usability problems in a focused task set using formative testing with a reasonably homogeneous user group.

OBrien2026

Gabrielle O’Brien, Alexis Parker, Nasir Eisty, and Jeffrey Carver: “A survey of generative AI adoption and perceived productivity among scientists who program.” (preprint), arxiv.org/abs/2512.19644.
Survey of 868 scientists who program as part of their work, reporting that 80% use GenAI tools in their programming, with 77.5% of those using general purposing tools like ChatGPT over specialised coding tools.

Peng2023

Sida Peng, Eirini Kalliamvakou, Peter Cihon, and Mert Demirer: “The Impact of AI on Developer Productivity: Evidence from GitHub Copilot.” 2023, 10.48550/arXiv.2302.06590.
Randomized controlled experiment claiming that GitHub Copilot users completed a JavaScript coding task 55.8% faster than the control group.

Sadowski2019

Caitlin Sadowski and Thomas Zimmermann (eds.): Rethinking Productivity in Software Engineering. Apress, 2019, 9781484242216.
Edited volume collecting research and practitioner perspectives on how to understand, define, and measure software developer productivity.