|Authors||T. Ma, S. Ali and T. Yue|
|Title||Conceptually Understanding Uncertainty in Self-Healing Cyber-Physical Systems|
|Project(s)||MBT4CPS: Model-Based Testing For Cyber-Physical Systems , The Certus Centre (SFI)|
|Publication Type||Technical reports|
|Year of Publication||2016|
|Publisher||Simula Research Laboratory|
|Keywords||Cyber-Physical Systems, Search-Based Software Engineering, Self-Healing, Testing, Uncertainty|
Smart Cyber-Physical Systems (CPSs) are autonomic systems capable of making decisions at runtime by themselves. These systems are complex in nature and typically operate in highly unpredictable and uncertain environments. One key autonomic capability of such systems is to recover from failures in an autonomic manner, referred to as self-healing. Due to the wide range of applications of smart CPSs in our daily life, self-healing behaviors of smart CPSs must be reliable even under uncertainty. Uncertainty and Self-Healing in CPS, in general, are understudied areas of research and thus as the first step towards understanding self-healing and uncertainty, we propose a conceptual model to understand key concepts including self-healing behaviors, uncertainties, and their relationships. Our ultimate objective is to provide a unified understanding of these concepts, which forms a foundation for additional analyses in the future such as testing. We validated the conceptual model with six case studies having self-healing behaviors from the literature and industry.