Automated recommendations for reducing unnecessary variability of technology architectures

Abstract

A technology architecture (TA) represents the technical infrastructure of a company and consists of hardware and software components. As the evolution of such TAs is typically uncoordinated, their complexity often grows with a company’s requirements. As a consequence, a variety of redundancies and architectural variants exist, which are not necessary for the architecture’s purpose. This leads to increased costs and higher effort for evolving and maintaining the entire IT landscape. To alleviate these problems, unnecessary variability has to be identified and reduced. As a manual approach requires high effort and is not feasible for largescale analysis, experts face a major challenge. For this purpose, we propose an automated approach, which provides experts with recommendations for restructurings of related TAs in order to reduce unnecessary variability. We show suitability of our approach by expert interviews and an industrial case study with real-world TAs.