Abstract
Context: Developer eXperience (Dev-X) focuses on ensuring a better experience for software developers, while still achieving development goals. Indeed, several existing studies suggest that improved Dev-X may actually result in improved development productivity. But a comprehensive understanding of how to empirically assess Dev-X remains limited. Aims and Method: This paper determines the empirical coverage of Dev-X facets to date by analyzing employed empirical designs and identifying quality issues or guidelines for assessing Dev-X. To this end, it presents a mapping study of 231 articles that employed empirical methods to explore the Dev-X landscape. Results: It identifies 16 facets of Dev-X—spanning emotions, values, and perceptions—and systematically maps the empirical methods, data types, and evaluation metrics used to assess these facets. The findings reveal gaps in facet coverage, highlight underutilized empirical designs, and stress the importance of quality assessment and methodological triangulation. This research offers a facet-wise synthesis of empirical designs and provides actionable guidelines to help researchers and practitioners empirically evaluate Dev-X. Conclusion: Based on SLR findings, this paper presents a Dev-X facet-based synthesis of empirical designs to guide selection of method, data, and metric combinations in future studies. By revealing design gaps (e.g., underexplored facets, overuse of surveys, weak corroboration) and highlighting dominant practices (e.g., survey-based ratings for emotions and values), our facet-wise schema offers an evidence-based guide for context-appropriate Dev-X evaluation strategies. Editor's note: Open Science material was validated by the Journal of Systems and Software Open Science Board.
| Original language | English |
|---|---|
| Article number | 112648 |
| Journal | Journal of Systems and Software |
| Volume | 233 |
| DOIs | |
| Publication status | Published - Mar 2026 |
Keywords
- Developer experience
- Developer tools
- Empirical analysis
- Human factors
- Software development
- Software engineering
- Software psychology
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