An Integrated Self-Testing Framework for Autonomic Computing Systems

As the technologies of autonomic computing become more prevalent, it is essential to develop methodologies for testing their dynamic self-management operations. Self-management features in autonomic systems induce structural and behavioral changes to the system during its execution, which need to be validated to avoid costly system failures. The high level of automation in autonomic systems also means that human errors such as incorrect goal specification could yield potentially disastrous effects on the components being managed; further emphasizing the need for runtime testing. In this paper the authors propose a self-testing framework for autonomic computing systems to dynamically validate change requests.