Learning of Reactive Systems
The goal of this project is to develop new and enhance existing techniques to automatically construct models of reactive systems. We look upon the system at hand as a black box, i.e., we have no access to code, we only see what we input to the system and what is output. "Model Learning", or also called "Model Inference", is an existing technique to from this knowledge about the system construct a model. The general idea is when having obtained a model of the system it will be analysed. This model can then be used for test-case generation, model checking, or further model-based analysis techniques.
The project is carried out by members of Uppsala's testing group. Please consult this page for information on group meetings, seminars, and our further activities.