Model-Driven Evaluation of Software Architecture Quality Using Model Clone Detection

Abstract

As software architecture methods and tools become increasingly model-driven, evaluating architecture artifacts must adjust correspondingly. Model-driven evaluation of architecture quality has advantages over traditional evaluation techniques, especially when applied in a model-driven context. One approach we found successful in performing model-driven analysis involves using model clone detection, whereby we detect subsystems that are similar to example systems that are positive and negative quality indicators. In this paper we present our ideas on applying model clone detection to realize model-driven evaluation of software architectures, which contain many high-level systems and interactions. We propose having model-based representations of architectural patterns and styles, and employing model clone detection to identify positive and negative architectural aspects for evaluation, including reliability and security. We provide our insights on how this research can be applied to popular architectural paradigms, relation to previous work, and present discussion points on how it will impact software architecture quality evaluation.