Uncertainties in the modeling of self-adaptive systems: a taxonomy and an example of availability evaluation

Abstract

The complexity of modern software systems has grown enormously in the past years with users always demanding for new features and better quality of service. Besides, software is often embedded in dynamic contexts, where requirements, environment assumptions, and usage profiles continuously change. As an answer to this need, it has been proposed the usage of self-adaptive systems. Self-adaptation endows a system with the capability to accommodate its execution to different contexts in order to achieve continuous satisfaction of requirements. Often, self-adaptation process also makes use of runtime model evaluations to decide the changes in the system. However, even at runtime, context information that can be managed by the system is not complete or accurate; i.e, it is still subject to some uncertainties. This work motivates the need for the consideration of the concept of uncertainty in the model-based evaluation as a primary actor, classifies the avowed uncertainties of self-adaptive systems, and illustrates examples of how different types of uncertainties are present in the modeling of system characteristics for availability requirement satisfaction.