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Taming Uncertainty in the Assurance Process of Self-Adaptive Systems: a Goal-Oriented Approach by Gabriela Felix Solano; Ricardo Diniz Caldas; Genaina Nunes Rodrigues; Thomas Vogel; Patrizio Pelliccione is a scholarly article available to read on EtoBox.

What is Taming Uncertainty in the Assurance Process of Self-Adaptive Systems: a Goal-Oriented Approach about?

Goals are first-class entities in a self-adaptive system (SAS) as they guide the self-adaptation. A SAS often operates in dynamic and partially unknown environments, which cause uncertainty that the SAS has to address to achieve its goals. Moreover, besides the environment, other classes of uncertainty have been identified. However, these various classes and their sources are not systematically addressed by current approaches throughout the life cycle of the SAS. In general, uncertainty typically makes the assurance provision of SAS goals exclusively at design time not viable. This calls for an assurance process that spans the whole life cycle of the SAS. In this work, we propose a goal-oriented assurance process that supports taming different sources (within different classes) of uncertainty from defining the goals at design time to performing self-adaptation at runtime. Based on a goal model augmented with uncertainty annotations, we automatically generate parametric symbolic formulae with parameterized uncertainties at design time using symbolic model checking. These formulae and the goal model guide the synthesis of adaptation policies by engineers. At runtime, the generated fo

Author

Gabriela Felix Solano; Ricardo Diniz Caldas; Genaina Nunes Rodrigues; Thomas Vogel; Patrizio Pelliccione

Publisher

IEEE

Published

2019

Language

EN