Summary of the dissertation

Self-learning systems that adapt their behavior individually to users during operation are becoming increasingly relevant - for example in vehicles that remember personal driving habits.

However, the validation of such dynamically learning functions poses considerable challenges for conventional test procedures.

This dissertation therefore presents a novel validation approach that combines realistic usage scenarios with intelligent test methods in order to test the behavior of self-adaptive systems in a targeted and comprehensible manner.

We would like to congratulate Marco Stang on this significant achievement and wish him all the best for his scientific and professional future.