Search Strategy to Update Systematic Literature Reviews in Software Engineering

[Context] Systematic Literature Reviews (SLRs) have been adopted within the Software Engineering (SE) domain for more than a decade to provide meaningful summaries of evidence on several topics. Many of these SLRs are now outdated, and there are no standard proposals on how to update SLRs in SE. [Objective] The goal of this paper is to provide recommendations on how to best to search for evidence when updating SLRs in SE. [Method] To achieve our goal, we compare and discuss outcomes from applying different search strategies to identifying primary studies in a previously published SLR update on effort estimation. [Results] The use of a single iteration forward snowballing with Google Scholar, and employing the original SLR and its primary studies as a seed set seems to be the most cost-effective way to search for new evidence when updating SLRs. [Conclusions] The recommendations can be used to support decisions on how to update SLRs in SE.