Towards Formal Modeling of Quality-driven Systems under uncertainty

Modern software systems tend to become increasingly complex and dynamic where unpredictable changes in user needs, in platforms and in execution contexts are unavoidable. Therefore, self-adaptation presents a promising approach for managing the complexity of current systems. One major objective of software engineering for self-adaptive systems is to deal with such complexity, changing contexts and mainly uncertainty, but still maintaining the quality requirements of the system, namely security, reliability, robustness, and so on. Uncertainty can be of various sources as the changeable environment and variability in resource availability. In this paper, we introduce a formal model for self-adaptive systems operating under uncertainty, in which we make use of both high-level petri nets and plausible petri nets, in order to help the designer to model systems that are capable of monitoring their operation and adapt their behavior when their contexts or environment change.