A Systematic Mapping Study on Quality Attribute Traceability

Abstract

Quality attribute traceability (QAT), as a sub-discipline of software traceability, ensures that quality attributes are considered in all phases of software development. QAT is one of the most critical and challenging research areas in requirement engineering. In recent years, several studies have been conducted on quality attribute traceability. However, researchers in this field have problems to identifying the research status of this field due to the lack of a comprehensive secondary study that reveals research trends and gaps. Evidence-based software engineering (EBSE) proposes systematic mapping study (SMS) and systematic literature review (SLR) methods for secondary studies on software engineering. In this paper we use the semantically enhanced SMS method in the QAT research area. In order to improve SMS, we introduce a concept classification approach. In this approach by using a QAT domain ontology, the keywords classification process is improved. The most important innovation of this study is the presentation of the QAT research tree. This research tree has been created by gathering research topics identified in this field along with existing gaps. Identified research topics include “QAT Approach,” “QAT Development,” “QAT Model,” “QAT Framework,” and “QAT Algorithm”. The results also indicate that “QAT Frameworks” is a research trend, and most recent studies have focused on this topic. On the other hand, “Trace Maintenance” and “Trace Integrity” are the research gaps in this field. In this article, active researchers, journals, conferences and countries in the field of QAT are also introduced. We also introduce a set of tools that facilitate the SMS process.