Dr. Istvan David

Digital twins are real-time virtual replicas of physical assets, typically used for real-time monitoring and control of complex systems, e.g., for energy-efficiency and resource optimization. This course provides an introduction to the foundational engineering areas required to develop digital twins: modeling and simulation for real-time reasoning, collecting and managing data to connect the digital twin to the physical system, and controlling the physical system through closed-loop control.
You will be exposed to the technical depths of these engineering areas and learn about their integration in specific digital twin architectures and lifecycle models. In addition to the lectures, you will process related scientific literature (from domains such as smart cities, industrial automation, or precision agriculture) to further customize your learning experience.

LIST G: COMPUTER SCIENCE Measurements. Unit testing, slicing and debugging, integration testing, regression testing, testing strategies, test coverage.

LIST G: COMPUTER SCIENCE Measurements. Unit testing, slicing and debugging, integration testing, regression testing, testing strategies, test coverage.

Software life cycle, quality attributes, requirements documentation, specifying behaviour; classes and objects, interface specification; creational patterns, structural design patterns, behavioural design patterns; implementation in code, reviews, testing and verification.