Analytikbasierter kontinuierlicher Microservice-API-Entwurf

As we enter the age of continuity, service-oriented software systems are not only open towards the rest of the world, but are expected to continuously evolve to deal with changing requirements and adapt to their dynamic environment and unpredictable workload. This project will focus on the critical element of such systems, the interface (or API), which decouples the internal implementation of every microservice from its consumers. The project will address the problem that APls continue to change together with the rest of the microservice architecture, but this becomes increasingly difficult and expensive, especially when having to ensure that each microservice can continue to independently undergo a high frequency stream of changes, supported by continuous delivery processes handling many releases a day.

The objective of the project is to establish a novel data-driven approach to the design and evolution of microservice APls where the expectations of API designers can be continuously validated against the actual usage of the API by the consumers. To do so, a deeper understanding of APls and the corresponding design processes is required, so that the impact of each decision on the quality of the resulting architecture can be estimated. Focusing on APls will allow us to reduce the complexity of the problems involved. In more detail, we plan to address the following research questions in our studies:

- How can API quality aspects be rigorously specified?
- How can API qualities be quantified beyond relying on manually created estimates?
- How can API qualities be checked in a rapid release context both within the delivery pipeline and at runtime? How can such checks be specified against a formal model of the API?
- How can a continuous feedback loop supporting the re-design of microservice APls be established supported by a rich set of API quality indicators, design heuristics and guidances to fix quality defects?

Answering these research questions will require us to rigorously specify APls in a holistic model. To better quantify API qualities we will establish the foundations of novel API analytics delivering a rich set of quality metrics and indicators. All critical quality issues will be further specified as formal constraints, and we will develop novel analysis methods to check them automatically. The outcome of API analytics and checks will indicate quality defects. These will enable us to close the feedback loop by mapping detected defects back to the formal models of the API, so that these can be contextualized and intuitively understood by human API designers and be used to automatically make redesign recommendations.

This project is funded by FWF (Austrian Science Fund), project API-ACE: I 4268.