A comparison of automated training-by-example selection algorithms for Evidence Based Software Engineering

摘要

Context: Study search and selection is central to conducting Evidence Based Software Engineering (EBSE) research, including Systematic Literature Reviews and Systematic Mapping Studies. Thus, selecting relevant studies and excluding irrelevant studies, is critical. Prior research argues that study selection is subject to researcher bias, and the time required to review and select relevant articles is a target for optimization.