Mapping study completeness and reliability - a case study

Abstract

Context: We have been undertaking a series of case studies to investigate the value of mapping (scoping) studies in software engineering. Our previous studies have assessed these using the subjective opinions of researchers. Objective: In order to provide a more objective assessment of value, for this study, we used the results of a systematic mapping study to investigate how well mapping studies identify clusters of related studies and to what extent such clusters are complete. Method: In this participant-observer case study, we undertook a mapping study of unit testing and regression testing empirical studies, which we compared with a previous expert literature review and with six other mapping studies and systematic literature reviews (SLRs) that addressed overlapping topics. Results: Our mapping study found more clusters than the expert literature review although it benefited from the set of studies identified by the expert review when refining our search process. The set of studies found by our searches were less complete than those found by SLRs addressing more specific topics, although we found some studies missed by those SLRs. Conclusions: Researchers undertaking systematic reviews and mapping studies should make use of related systematic reviews and mapping studies to identify known studies in order to refine search strings and validate search results. For completeness and traceability, mapping studies should keep a record of all multiple reports of a single study. Meta-analyses and other systematic literature reviews undertaking detailed aggregation should report on candidate primary studies that were rejected in the final screening process, as well as candidate studies that were included. This helps ensure the repeatability of aggregation results.