Evaluation of resilience in self-adaptive systems using probabilistic model-checking

Abstract

The provision of assurances for self-adaptive systems presents its challenges since uncertainties associated with its operating environment often hamper the provision of absolute guarantees that system properties can be satisfied. In this paper, we define an approach for the verification of self-adaptive systems that relies on stimulation and probabilistic model-checking to provide levels of confidence regarding service delivery. In particular, we focus on resilience properties that enable us to assess whether the system is able to maintain trustworthy service delivery in spite of changes in its environment. The feasibility of our proposed approach for the provision of assurances is evaluated in the context of the Znn.com case study.