🤖 AI Summary
This study addresses the persistent gap between systematic literature reviews (SLRs) in software engineering and their practical uptake in industry, often referred to as the evidence-to-practice translation gap. To bridge this divide, the work introduces the Evidence to Decision (EtD) framework—originally developed in health sciences—into software engineering for the first time. By convening expert panels to conduct structured evaluations of SLR evidence against multidimensional criteria, the approach generates practitioner-oriented evidence briefs and actionable recommendations. This methodology strengthens the mechanism for translating research findings into real-world decisions, offering the first application of EtD in software engineering, identifying key dimensions essential for generating trustworthy recommendations, and highlighting major challenges that must be addressed for broader adoption of the framework.
📝 Abstract
Over twenty years ago, the Software Engineering (SE) research community have been involved with Evidence-Based Software Engineering (EBSE). EBSE aims to inform industrial practice with the best evidence from rigorous research, preferably from systematic literature reviews (SLRs). Since then, SE researchers have conducted many SLRs, perfected their SLR procedures, proposed alternative ways of presenting their results (such as Evidence Briefings), and profusely discussed how to conduct research that impacts practice. Nevertheless, there is still a feeling that SLRs' results are not reaching practitioners. Something is missing. In this vision paper, we introduce Evidence to Decision (EtD) frameworks from the health sciences, which propose gathering experts in panels to assess the existing best evidence about the impact of an intervention in all relevant outcomes and make structured recommendations based on them. The insight we can leverage from EtD frameworks is not their structure per se but all the relevant criteria for making recommendations to practitioners from SLRs. Furthermore, we provide a worked example based on an SE SLR. We also discuss the challenges the SE research and practice community may face when adopting EtD frameworks, highlighting the need for more comprehensive criteria in our recommendations to industry practitioners.