Architecture-centric software evolution by software metrics and design patterns

Abstract

It is shown how software metrics and architectural patterns can be used for the management of software evolution. In the presented architecture-centric software evolution method the quality of a software system is assured in the software design phase by computing various kinds of design metrics from the system architecture, by automatically exploring instances of design patterns and anti-patterns from the architecture, and by reporting potential quality problems to the designers. The same analysis is applied in the implementation phase to the software code, thus ensuring that it matches the quality and structure of the reference architecture. Finally, the quality of the ultimate system is predicted by studying the development history of previous projects with a similar composition of characteristic software metrics and patterns. The architecture-centric software evolution method is supported by two integrated software tools, the metrics and pattern-mining tool Maisa and the reverse-engineering tool Columbus.