An Empirical Approach

this paper, we describe a set of methods and techniques that we have developed and adapted to empirically study software evolution. Our longitudinal empirical study involves collecting, coding, and analyzing more than 25,000 change events to 23 commercial software systems over a 20-year period. Using data from two of the systems, we illustrate the efficacy of flexible phase mapping and gamma sequence analytic methods originally developed in social psychology to examine group problem solving processes. We have adapted these techniques in the context of our study to identify and understand the phases through which a software system travels as it evolves over time. We contrast this approach with time series analysis, the more traditional way of studying longitudinal data. Our work demonstrates the advantages of applying methods and techniques from other domains to software engineering and illustrates how, despite difficulties, software evolution can be empirically studie