🤖 AI Summary
This study addresses collaboration friction between domain experts (DEs) and software developers (SDEs) in cross-disciplinary software development (CDSD), stemming from misaligned expectations. Using activity theory as an analytical framework, we employed a mixed-methods approach—combining semi-structured interviews with large-scale questionnaire surveys—to empirically identify six core expectations of DEs and eight of SDEs, and to systematically categorize 21 typical friction points and their conflict patterns. Our key contribution is the first activity-theoretic, actionable diagnostic model for cross-disciplinary collaboration, which explicates how expectation discrepancies translate into practical conflicts via mediating elements—including tools, rules, and division of labor. The findings provide both theoretical grounding and practical guidance for role alignment, process design, and collaborative mechanism optimization in CDSD teams.
📝 Abstract
Background: Software development teams are increasingly diverse, embedded, and cross-disciplinary. Domain experts (DEs) from different disciplines collaborate with professional software developers (SDEs), bringing complementary expertise in creating and maintaining complex production software. However, contested expectations, divergent problem-solving perspectives, and conflicting priorities lead to friction. Aims: This study aims to investigate the dynamics of emerging collaboration of cross-disciplinary software development (CDSD) by exploring the expectations held by DEs and SDEs and understanding how these frictions manifest in practice. Method: We utilize Activity Theory (AT), a well-established socio-technical framework, as an analytical lens in a grounded, empirical investigation, conducted through a mixed-method study involving 24 interviews (12 DEs and 12 SDEs) and a large-scale validation survey with 293 participants (161 DEs and 132 SDEs). Results: We conceptualize and empirically ground the CDSD dynamics. We identified eight expectations held by SDEs and six by DEs. By mapping these expectations to AT components, we revealed 21 frictions in CDSD and illustrated where and how they arise. Conclusions: This study offers a theoretical lens for understanding the dynamics and frictions in CDSD and provides actionable insights for future research, practitioners, and infrastructure design.