Empirical Software Engineering: From Discipline to Interdiscipline

TL;DR

This paper critically examines the shift of empirical software engineering towards an interdisciplinary approach, emphasizing the need for symmetric collaboration and new research configurations to address human-centric challenges.

Contribution

It proposes a pragmatic, cyclic view of empirical research as an interdisciplinary configuration, offering rules of thumb for effective collaboration.

Findings

Highlights the importance of interdisciplinary research in empirical software engineering.

Proposes a cyclic, pragmatic model for knowledge creation in the field.

Identifies challenges and rules for symmetric interdisciplinary collaboration.

Abstract

Empirical software engineering has received much attention in recent years and coined the shift from a more design-science-driven engineering discipline to an insight-oriented, and theory-centric one. Yet, we still face many challenges, among which some increase the need for interdisciplinary research. This is especially true for the investigation of human-centric aspects of software engineering. Although we can already observe an increased recognition of the need for more interdisciplinary research in (empirical) software engineering, such research configurations come with challenges barely discussed from a scientific point of view. In this position paper, we critically reflect upon the epistemological setting of empirical software engineering and elaborate its configuration as an Interdiscipline. In particular, we (1) elaborate a pragmatic view on empirical research for software engineering reflecting a cyclic process for knowledge creation, (2) motivate a path towards symmetrical interdisciplinary research, and (3) adopt five rules of thumb from other interdisciplinary collaborations in our field before concluding with new emerging challenges. This shall support stopping to treating empirical software engineering as a developing discipline moving towards a paradigmatic stage of normal science, but as a configuration of symmetric interdisciplinary teams and research methods.