An empirically based terminology and taxonomy for global software engineering

Many organizations nowadays strive for utilization of benefits offered by global software engineering (GSE) and sourcing strategies are thus discussed more often. Since there are so many variations of the attributes associated with global software projects a large amount of new terms has been introduced. The diversity in sourcing jargon however has caused difficulties in determining which term to use in which situation, and thus causing further obstacles to searching and finding relevant research during e.g. systematic literature reviews. The inability of judging the applicability of the research in an industrial context is another important implication on the transferability of research into practice. Thus the need for accurate terminology and definitions for different global sourcing situations emerges as a way for the community to build upon each other’s work and hence making progress more quickly. In this paper we first investigate the state of the use of the GSE jargon concluding that terminology is very diverse (many synonyms used to describe the same phenomena), often confusing (same terms used to describe different phenomena) and occasionally ambiguous (few terms used to describe several phenomena). In order to address the identified problems, we conducted a Delphi-inspired study with ten well-established researchers in GSE and developed an empirically based glossary for the key concepts in global software engineering. We then propose a taxonomy for GSE by categorizing the selected terms based on generalization-specialization relationships and illustrate how the taxonomy can be used to categorize and map existing knowledge. The contribution targets future researchers, who will publish or synthesize further empirical work and practitioners, who are interested in published empirical cases. Therefore this work is expected to make a contribution to the future development of research in the GSE field, and alleviate understandability and transferability of existing and future knowledge into practice.