Bayesian Synthesis for Knowledge Translation in Software Engineering : Method and Illustration

Systematic literature reviews in software engineering are necessary to synthesize evidence from multiple studies to provide knowledge and decision support. However, synthesis methods are underutilized in software engineering research. Moreover, translation of synthesized data (outcomes of a systematic review) to provide recommendations for practitioners is seldom practiced. The objective of this paper is to introduce the use of Bayesian synthesis in software engineering research, in particular to translate research evidence into practice by providing the possibility to combine contextualized expert opinions with research evidence. We adopted the Bayesian synthesis method from health research and customized it to be used in software engineering research. The proposed method is described and illustrated using an example from the literature. Bayesian synthesis provides a systematic approach to incorporate subjective opinions in the synthesis process thereby making the synthesis results more suitable to the context in which they will be applied. Thereby, facilitating the interpretation and translation of knowledge to action/application. None of the synthesis methods used in software engineering allows for the integration of subjective opinions, hence using Bayesian synthesis can add a new dimension to the synthesis process in software engineering research