Taster is an experimental tool designed for leveraging the principles of model-based testing and their application in the process of integration testing of automotive systems. Its modeling language is based on the popular formalism of timed automata networks and is compatible with the modeling language used by the UPPAAL model checker. Additionally, Taster is utilizing principles of machine learning and perception for enhancement of the testing process. The tool was built using modern technologies, including C# programming language, ML.NET machine learning framework, and .NET ecosystem.

Taster is still under active development, and our team continually seeks students eager to aid us with its development. Participants on its development can help with the implementation of additional testing strategies, as well as with enhancements of the existing code base, user interface, and integration with testing back-end technologies.