Skip to main content
Kent Academic Repository

Robustness-Driven Resilience Evaluation of Self-Adaptive Software Systems

Cámara, Javier, de Lemos, Rogerio, Laranjeiro, Nuno, Ventura, Rafael, Vieira, Marco (2015) Robustness-Driven Resilience Evaluation of Self-Adaptive Software Systems. IEEE Transactions on Dependable and Secure Computing, 14 (1). pp. 50-64. ISSN 1545-5971. E-ISSN 1941-0018. (doi:10.1109/TDSC.2015.2429128) (KAR id:50275)


An increasingly important requirement for certain classes of software-intensive systems is the ability to self-adapt their structure and behavior at run-time when reacting to changes that may occur to the system, its environment, or its goals. A major challenge related to self-adaptive software systems is the ability to provide assurances of their resilience when facing changes. Since in these systems, the components that act as controllers of a target system incorporate highly complex software, there is the need to analyze the impact that controller failures might have on the services delivered by the system. In this paper, we present a novel approach for evaluating the resilience of self-adaptive software systems by applying robustness testing techniques to the controller to uncover failures that can affect system resilience. The approach for evaluating resilience, which is based on probabilistic model checking, quantifies the probability of satisfaction of system properties when the target system is subject to controller failures. The feasibility of the proposed approach is evaluated in the context of an industrial middleware system used to monitor and manage highly populated networks of devices, which was implemented using the Rainbow framework for architecture-based self-adaptation.

Item Type: Article
DOI/Identification number: 10.1109/TDSC.2015.2429128
Uncontrolled keywords: resilience evaluation, self-adaptive systems, robustness testing techniques, probabilistic model checking
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Rogerio de Lemos
Date Deposited: 21 Aug 2015 15:33 UTC
Last Modified: 16 Feb 2021 13:27 UTC
Resource URI: (The current URI for this page, for reference purposes)

University of Kent Author Information

  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.