Reporting Empirical Evidence in Distributed Software Development: An Extended Taxonomy

Distributed Software Development (DSD) has been discussed by industry and academia for almost two decades now, and, as consequence, there is a large number of empirical scientific papers and industrial reports on it. However, the description of the context in which the empirical study was conducted is not always clear or complete, making the process of searching for empirical evidence burdensome. It becomes difficult to understand or to judge the relevance of study given that DSD scenarios are diverse. What works in one context might not apply to another. To reduce such difficulty, we need, as a research community, to have means to standardize how we report empirical studies and their findings aiming to make them more readily available to practitioners and researchers. In this paper we present an extended taxonomy to classify empirical DSD evidence. We conducted an expert opinion survey with researchers and practitioners to identify elements to compose the taxonomy. Preliminary evaluation of the proposed taxonomy suggests that it can be used to synthesize existing knowledge, to identify gaps in literature, to identify related work and to help researchers who will publish or review further empirical work, as well as practitioners who are interested in published empirical studies.