A framework for acquisition and application of software architecture evolution knowledge: 14
ACM SIGSOFT Software Engineering Notes
Towards a pattern language for self-adaptation of cloud-based architectures
Proceedings of the WICSA 2014 Companion Volume
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Context: Software systems are increasingly required to operate in an open world, characterized by continuous changes in the environment and in the prescribed requirements. Architecture-centric software evolution (ACSE) is considered as an approach to support software adaptation at a controllable level of abstraction in order to survive in the uncertain environment. This requires evolution in system structure and behavior that can be modeled, analyzed and evolved in a formal fashion. Existing research and practices comprise a wide spectrum of evolution-centric approaches in terms of formalisms, methods, processes and frameworks to tackle ACSE as well as empirical studies to consolidate existing research. However, there is no unified framework providing systematic insight into classification and comparison of state-of-the-art in ACSE research. Objective: We present a taxonomic scheme for a classification and comparison of existing ACSE research approaches, leading to a reflection on areas of future research. Method: We performed a systematic literature review (SLR), resulting in 4138 papers searched and 60 peer-reviewed papers considered for data collection. We populated the taxonomic scheme based on a quantitative and qualitative extraction of data items from the included studies. Results: We identified five main classification categories: (i) type of evolution, (ii) type of specification, (iii) type of architectural reasoning, (iv) runtime issues, and (v) tool support. The selected studies are compared based on their claims and supporting evidences through the scheme. Conclusion: The classification scheme provides a critical view of different aspects to be considered when addressing specific ACSE problems. Besides, the consolidation of the ACSE evidences reflects current trends and the needs for future research directions.