Rapid Reviews in Software Engineering
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Abstract (arXiv)
Integrating research evidence into practice is one of the main goals of Evidence-Based Software Engineering (EBSE). Secondary studies, one of the main EBSE products, are intended to summarize the best research evidence and make them easily consumable by practitioners. However, recent studies show that some secondary studies lack connections with software engineering practice. In this chapter, we present the concept of Rapid Reviews, which are lightweight secondary studies focused on delivering evidence to practitioners in a timely manner. Rapid reviews support practitioners in their decision-making, and should be conducted bounded to a practical problem, inserted into a practical context. Thus, Rapid Reviews can be easily integrated in a knowledge/technology transfer initiative. After describing the basic concepts, we present the results and experiences of conducting two Rapid Reviews. We also provide guidelines to help researchers and practitioners who want to conduct Rapid Reviews, and we finally discuss topics that my concern the research community about the feasibility of Rapid Reviews as an Evidence-Based method. In conclusion, we believe Rapid Reviews might interest researchers and practitioners working in the intersection between software engineering research and practice.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Mar 2020.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 0; 2025: 1; 2026: 3.
5 papers.
- 2022Exploring ML testing in practice -- Lessons learned from an interactive rapid review with Axis Communicationscited by 3
- 2025Toward Effective AI Governance: A Review of Principlescited by 2
- 2026Fairness in Multi-Agent Systems for Software Engineering: An SDLC-Oriented Rapid Reviewcited by 0
- 2026Fairness Definitions and Metrics in Deep Reinforcement Learning for Drug Discovery in Healthcare: A Rapid Evidence Reviewcited by 0
- 2026Human Oversight and Overload: Two Hidden and Costly Burdens of AI-Assisted Software Engineeringcited by 0
- 2026Human Oversight and Overload: Two Hidden and Costly Burdens of AI-Assisted Software Engineering4 Jun 2026
- 2026Fairness Definitions and Metrics in Deep Reinforcement Learning for Drug Discovery in Healthcare: A Rapid Evidence Review1 Jun 2026
- 2026Fairness in Multi-Agent Systems for Software Engineering: An SDLC-Oriented Rapid Review10 Apr 2026
- 2025Toward Effective AI Governance: A Review of Principles29 May 2025
- 2022Exploring ML testing in practice -- Lessons learned from an interactive rapid review with Axis Communications30 Mar 2022