An Exploratory Study of Naturalistic Decision Making in Complex Software Architecture Environments

Abstract

Architects always make decisions in some context. That context shifts and changes dynamically. Different decision-making strategies are appropriate in different contexts. Architecture decisions are at times made under conditions of time pressure, high stakes, uncertainty, and with too little information. At other times, decision-makers have sufficient time to reflect on the decision and consider alternatives. Understanding context is critical to choosing appropriate approaches to architecture decision making. Naturalistic Decision Making (NDM) explains how people make decisions under real-world conditions. This paper investigates NDM in software architecture and studies architecture decisions in their environment and decision-making context. The research approach includes a case study of large technology organizations consisting of a survey, multiple focus groups, and participant observation. Previous studies that touch on NDM in software architecture have mainly focused on decision-making processes or tools or developing decision models. This paper provides three contributions. First, we build on previous studies by other researchers to produce an in-depth exploration of NDM in the context of software architecture. We focus on Recognition-Primed Decision (RPD) making as an implementation of NDM. Second, we present an examination of the decisions made by experienced architects under conditions that can be considered naturalistic. Third, we provide examples and recommendations that help software architects determine when an NDM approach is appropriate for their context.