An exploration of evolutionary change in an example of scientific software

• Authors: Diane Frances Kelly
• Venue: An exploration of evolutionary change in an example of scientific software
• Year: 2004

Scientific software is typically long lived and does not seem to decay, despite high complexity and a relative lack of textbook software engineering practices. The study of such software may provide useful guidance for the evolution of other kinds of software. There is a wealth of examples to study. Unfortunately, most lack historical documentation, so new techniques have to be found to do longitudinal evolutionary studies. This thesis develops a change identification technique based on examining changes in the central data structures of the software. This technique is used to examine change in a particular example of successful, long-lived scientific software. Change is classified and analysed using a new change model, which is based on the idea that drivers for change come from a set of knowledge domains and are filtered by factors present in the environment, including the software itself. The combination of change drivers and change filters successfully accounts for the distribution of changes as observed. The thesis then considers the response of the original software design to changes that happened over roughly a 20 year period. A set of metrics is used to quantify the impacts of the changes, and to search for patterns of stability among a base version and three later versions of the software. Surprisingly, given the very different forces at work on the four versions, some interesting patterns of stability emerge. Some of the results of the thesis challenge established practices, such as the relative importance of information hiding, or the need to do extra work to prevent decay.