Iosif Itkin, Nikolay Dorofeev, Stanislav Glushkov, Alexey Yermolayev and Elena Treshcheva, Exactpro
The focus area of this research is around tools and methods of reconciliation testing, an approach to software testing that relies on the data reconciliation concept. The importance of such a test approach is steadily increasing across different knowledge domains, triggered by growing data volumes and overall complexity of present-day software systems. The paper describes the software implementation created as part of the authors’ industrial experience with data streaming analysis for the task of reconciliation testing of complex financial technology systems. The described solution is a Python-based component of an open-source test automation framework build as a Kubernetes-based microservices platform. The paper outlines the advantages and disadvantages of the approach as well as compares it to existing state-of-the-art solutions allowing for data streaming analysis and reconciliation checks.