The SPACE of Developer Productivity: There's more to it than you think.
Open accessAbstract
Developer productivity is about more than an individual's activity levels or the efficiency of the engineering systems relied on to ship software, and it cannot be measured by a single metric or dimension. The SPACE framework captures different dimensions of productivity, and here we demonstrate how this framework can be used to understand productivity in practice and why using it will help teams better understand developer productivity and create better measures to inform their work and teams.
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Current thinking in software engineering research suggests measuring productivity on multiple dimensions and using self-reported data.
“This meshes well with current thinking in software engineering research which suggests measuring productivity on multiple dimensions and using self-reported data [6].”
From Productivity Assessment of Neural Code Completion (2022) · cites this paper as [6]
A more holistic picture of productivity is formed by measuring perceived productivity through self-reported data across various dimensions and supplementing it with automatically measured data.
“A more holistic picture is formed by measuring perceived productivity through self-reported data across various dimensions [6], and supplementing it with automatically measured data [4].”
From Productivity Assessment of Neural Code Completion (2022) · cites this paper as [6]
The SPACE framework defines 5 dimensions of productivity: Satisfaction and well-being, Performance, Activity, Communication and Collaboration, Efficiency and Flow.
“The SPACE framework [6] defines 5 dimensions of productivity: Satisfaction and well-being, Performance, Activity, Communication and Collaboration, Efficiency and Flow.”
From Productivity Assessment of Neural Code Completion (2022) · cites this paper as [6]
Developer productivity is inherently complex and multidimensional, shaped not only by tools and tasks, but also by team dynamics and the work environment.
“Developer productivity is inherently complex and multidimensional, shaped not only by tools and tasks, but also by team dynamics and the work environment (Forsgren et al., 2021).”
From Developer Productivity With and Without GitHub Copilot: A Longitudinal Mixed-Methods Case Study (2026) · cites this paper as Forsgren et al., 2021
The survey was developed based on GitHub Research's survey, which employed the SPACE framework to evaluate how participants who used a technical preview of Copilot perceived their own productivity.
“The survey was developed based on GitHub Research's survey [28], which employed the SPACE framework [7] to evaluate how participants who used a technical preview of Copilot perceived their own productivity.”
From Human-AI Collaboration in Software Development: A Mixed-Methods Study of Developers' Use of GitHub Copilot and ChatGPT (2025) · cites this paper as [7]
We rely on the SPACE framework to discuss productivity in the context of software maintenance and evolution.
“In this study, we rely on the SPACE framework by Forsgren et al. (2021 ) to discuss productivity in the context of software maintenance and evolution.”
From Echoes of AI: Investigating the downstream effects of AI assistants on software maintainability (2026) · cites this paper as Forsgren et al. (2021)
The study focused on time on task as encouraged by Hernandez-Lopez et al., who found it to be one of the dominant measures of productivity in software engineering literature.
“our study focuses on time on task, as encouraged by Hern´ andez-L´ opez and colleagues, who found it to be one of the dominant measures of productivity in the software engineering literature [33].”
From How Much Does AI Impact Development Speed? an Enterprise-Based Randomized Controlled Trial (2025) · cites this paper as [33]
The Efficiency and flow and FRAMEWORK IN ACTION sections discuss time-based productivity metrics, but neither says time on task is a dominant measure in software engineering literature. Searches for that finding and for Hernández-López found no passage in our copy attributing it to those authors. (LLM, conf=0.73)
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Self-citation
- Authors
- Forsgren, N., Storey, M.-A., Maddila, C., Zimmermann, T., Houck, B., & Butler, J.
- Affiliations
- Global Health Strategies (United States) (US)
- University of Victoria (CA)
- Microsoft (United States) (US)
- ORCID
- Venue
- Queue
- Published
- 2021-02-28
- Volume
- 19
- Issue
- 1
- Pages
- 20-48
- ISSN
- 1542-7730 (ISSN-L)
- 1542-7749
- OpenAlex
- W3135708166
- Cited by
- 164
- References
- 23
- Citations by year
- 2026: 47 · 2025: 35 · 2024: 31 · 2023: 28 · 2022: 17 · 2021: 6
- FWCI
- 18.54
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Queue (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Social Sciences › Psychology › Social Psychology › Team Dynamics and Performance
- Keywords
- developer productivity, SPACE framework, software development teams, productivity measurement, software metrics, team performance
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