Managing API Evolution in Microservice Architecture

Nowadays, many software systems are split into loosely coupled microservices only communicating via Application Programming Interfaces (APIs) to improve maintainability, scalability, and fault tolerance. However, the loose coupling between microservices provides no immediate feedback on breaking API changes, and consuming services break or exhibit unexpected behavior only after the first actual call to the changed API. Hence, development teams must actively identify and communicate all breaking changes to affected teams to stay compatible. This research addresses this problem with three contributions. First, we identified API evolution strategies and open challenges in practice with an explorative study. Based on the study findings, we formulated two open research directions for evolving publicly accessible APIs, i.e., REpresentational State Transfer (REST) APIs. As the second contribution, we will introduce a REST API change extraction approach to improve the change notification accuracy. We plan experiments on open-source projects to evaluate our approach's accuracy and compare it to openapi-diff for structural changes. Third, we plan to investigate methods for automating communication with affected teams, which will then improve the change notification reliability. Finally, we will evaluate the accuracy and reliability of our notifications with a user study.