Change propagation in large technical systems

Abstract

Propagation of engineering changes has gained increasing scrutiny as the complexity and scale of engineered systems has increased. Over the past decade academic interest has risen, yielding some small-scale in-depth studies, as well as a variety of tools aimed at aiding investigation, analysis and prediction of change propagation. This thesis applies many of the methods and seeks to apply and extend prior reasoning through examination of a large data set from industry, including data from more than 41,000 change requests (most technical, but others not) over nearly a decade. Different methods are used to analyze the data from a variety of perspectives, in both the technical and managerial realms, and the results are compared to each other and evaluated in the context of previous findings. Macro-level patterns emerge independent of smaller scale data patterns, and in many cases offer clear implications for technical management approaches for large, complex systems development.