Using rapid reviews to support software engineering practice: a systematic review and a replication study

Pizard, Sebastián; Lezama, Joaquín; García, Rodrigo; Vallespir, Diego; Kitchenham, Barbara

Abstract

Context
A few years ago, rapid reviews (RR) were introduced in software engineering (SE) to address the problem that standard systematic reviews take too long and too much effort to be of value to practitioners. Prior to our study, few practice-driven RRs had been reported, and none involved collaboration with practitioners lacking SE research experience.

Objective
To investigate practitioners’ perspectives on the use of RRs in supporting SE practices, we aimed to validate and build upon the findings of the seminal RR in SE study, specifically considering practitioners without explicit SE research experience.

Method
First, we studied previously conducted RRs in SE through a systematic review. Second, we carried out an external replication of the first study that proposed the use of RRs in SE. Specifically, we conducted an RR for an agile software development team looking to improve its knowledge management practices.

Results
Most of the software development team’s perceptions about RR results were positive and strongly consistent with previous research. In particular, RR results were considered more reliable than other sources of information and adequate to address the problems detected. Some months later they confirmed using some of the recommendations.

Conclusions
The results show that practitioners without explicit SE research experience appreciate the value of evidence and can make use of the results of RRs. However, SE research may need to be translated from broad recommendations to specific process change options. Our research also reveals that SE RRs reporting needs to be substantially improved.

Citation

Pizard, S., Lezama, J., García, R., Vallespir, D., & Kitchenham, B. (2025). Using rapid reviews to support software engineering practice: a systematic review and a replication study. Empirical Software Engineering, 30(1), https://doi.org/10.1007/s10664-024-10545-6

• Journal Article Type: Article
• Acceptance Date: Sep 10, 2024
• Online Publication Date: Oct 25, 2024
• Publication Date: 2025-02
• Deposit Date: Nov 12, 2024
• Journal: Empirical Software Engineering
• Print ISSN: 1382-3256
• Electronic ISSN: 1573-7616
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 30
• Issue: 1
• DOI: https://doi.org/10.1007/s10664-024-10545-6
• Public URL: https://keele-repository.worktribe.com/output/975478
• Publisher URL: https://link.springer.com/article/10.1007/s10664-024-10545-6
• Additional Information: Accepted: 10 September 2024; First Online: 25 October 2024; : ; : The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper