Main research findings
Self-healing is becoming a critical feature of Cyber-Physical Systems (CPSs). By detecting faults and applying recovery adaptations at runtime, self-healing behaviors can help CPSs to maintain functional normal in the presence of faults. CPSs with the self-healing feature are named as Self-Healing CPSs (SH-CPSs). Besides recovery, SH-CPSs have to deal with various uncertainties, such as measurement errors from sensors and actuation deviations from actuators. To assess the dependability of SH-CPSs, it is necessary to test if SH-CPSs can still behave as expected under uncertainty. However, the autonomy of self-healing behaviors and the impact of uncertainties make it challenging to conduct such testing. To this end, an executable model-based testing approach is proposed in this thesis. In this approach, the expected behaviors of the SH-CPS under test are specified as an executable test model. By executing the SH-CPS together with the test model, sending them the same test inputs, and comparing their consequent states, we can dynamically test the system against its test model. To detect failures in the most effective manner, reinforcement learning algorithms have been applied with the new testing approach to learn the optimal testing policy. Evaluation results have demonstrated the effectiveness of the new testing approach.
The work has been conducted at Simula Research Laboratory and UiO.
Prior to the defence, Tao Ma presented his trial lecture «AI in Software Engineering».
The PhD defence and trial lecture were fully digital.
- Senior researcher Mehrdad Saadatmand,RISE Research Institutes of Sweden
- Associate Professor Ana Cristina Ramada Paiva,Informatics Engineering Department of the Faculty of Engineering of University of Porto (FEUP)
- Professor Yan Zhang,Department of Informatics, University of Oslo, Norway
- Adjunct Research Scientist Tao Yue,Simula Research Laboratory, Norway
- Chief Research Scientist Shaukat Ali,Simula Research Laboratory, Norway
Chair of defence
- ProfessorStephan Oepen, Department of Informatics, UiO