Reducing variability of technically related software systems in large-scale IT landscapes

The number of software systems in a company typically grows with the business requirements. Therefore, IT landscapes in large companies can consist of hundreds or thousands of different software systems. As the evolution of such large-scale landscapes is often uncoordinated, they commonly comprise different groups of related software systems using a common core technology (e.g., Java Web-Application) implemented by a variety of architectural components (e.g., different application servers or databases). This leads to increased costs and higher effort for maintaining and evolving these software systems and the entire IT landscape. To alleviate these problems, the variability of such technically related software systems has to be reduced. For this purpose, experts have to assess and evaluate restructuring potentials in order to take appropriate restructuring decisions. As a manual analysis requires high effort and is not feasible for large-scale IT landscapes, experts face a major challenge. To overcome this challenge, we introduce a novel approach to automatically support experts in taking reasonable restructuring decisions. By providing automated methods for assessing, evaluating and simulating restructuring potentials, experts are capable of reducing the variability of related software systems in large-scale IT landscapes. We show suitability of our approach by expert interviews and an industrial case study with architectures of real-world software systems.