2019/08/29 by Danny Weyns, Weyns, Danny, M. Usman Iftikhar +1 · 1 citation
Computer Science · #Advanced Software Engineering Methodologies #Software System Performance and Reliability #Service-Oriented Architecture and Web Services
paper · pdf · doi:10.48550/arxiv.1908.11179
Self-adaptation equips a computing system with a feedback loop that enables\nit dealing with change caused by uncertainties during operation, such as\nchanging availability of resources and fluctuating workloads. To ensure that\nthe system complies with the adaptation goals, recent research suggests the use\nof formal techniques at runtime. Yet, existing approaches have three\nlimitations that affect their practical applicability: (i) they ignore\ncorrectness of the behavior of the feedback loop, (ii) they rely on exhaustive\nverification at runtime to select adaptation options to realize the adaptation\ngoals, which is time and resource demanding, and (iii) they provide limited or\nno support for changing adaptation goals at runtime. To tackle these\nshortcomings, we present ActivFORMS (Active FORmal Models for Self-adaptation).\nActivFORMS contributes an end-to-end approach for engineering self-adaptive\nsystems, spanning four main stages of the life cycle of a feedback loop:\ndesign, deployment, runtime adaptation, and evolution. We also present\nActivFORMS-ta, a tool-supported instance of ActivFORMS that leverages timed\nautomata models and statistical model checking at runtime. We validate the\nresearch results using an IoT application for building security monitoring that\nis deployed in Leuven. The experimental results demonstrate that ActivFORMS\nsupports correctness of the behavior of the feedback loop, achieves the\nadaptation goals in an efficient way, and supports changing adaptation goals at\nruntime.\n