Model based testing with machine learning techniques
We are interested in a variety of topics in the applications of intelligent methods (e.g., machine learning and search algorithms) for engineering complex software systems. Example of these topics include:
- Using model execution and machine learning techniques (e.g., reinforcement learning) to cost-effectively test Cyber-Physical Systems (CPSs) or IoT in the presence of environmental uncertainty.
- Testing machine learning algorithms in software systems such as embedded in autonomous vehicles.
- Testing security and privacy of critical infrastructures, e.g., used in oil & gas, healthcare welfare technologies, and cancer registry system.
Developing software testing tools for the above topics. There is a possibility to apply the tools to the real case studies.
- Software Testing
- Machine Learning (e.g., active and passive learning)
- Search Algorithms (e.g., Genetic Algorithms)
- Model-based Testing
- Shaukat Ali
- Tao Yue