An empirical study of speed and communication in globally distributed software development

TLDR

Global software development is rapidly becoming the norm for technology companies, and prior qualitative research indicates that distributed development may increase cycle time for individual work items. The study models the extent of delay in a distributed software development organization using source‑code change management data and survey data, and explores possible mechanisms for this delay. The authors analyze change data from two organizations and survey results on social networks to identify mechanisms, confirming that distributed work involves more people and that social network differences relate to delay. Distributed work items take roughly 2.5 times longer than colocated ones because they involve more people, and analysis across two organizations confirms this, while survey data also reveal social network differences that may contribute to delay, suggesting that practices and collaboration tools could dramatically speed distributed development.

Abstract

Global software development is rapidly becoming the norm for technology companies. Previous qualitative research suggests that distributed development may increase development cycle time for individual work items (modification requests). We use both data from the source code change management system and survey data to model the extent of delay in a distributed software development organization and explore several possible mechanisms for this delay. One key finding is that distributed work items appear to take about two and one-half times as long to complete as similar items where all the work is colocated. The data strongly suggest a mechanism for the delay, i.e., that distributed work items involve more people than comparable same-site work items, and the number of people involved is strongly related to the calendar time to complete a work item. We replicate the analysis of change data in a different organization with a different product and different sites and confirm our main findings. We also report survey results showing differences between same-site and distributed social networks, testing several hypotheses about characteristics of distributed social networks that may be related to delay. We discuss implications of our findings for practices and collaboration technology that have the potential for dramatically speeding distributed software development.