Assuring system goals under uncertainty with active formal models of self-adaptation

Abstract

Designing software systems with uncertainties, such as incomplete knowledge about changing system goals, is challenging. One approach to handle uncertainties is self-adaptation, where a system consists of a managed system and a managing system that realizes a feedback loop. The promise of self-adaptation is to enable a system to adapt itself realizing the system goals, regarding uncertainties. To realize this promise it is critical to provide assurances for the self-adaptive behaviours. Several approaches have been proposed that exploit formal methods to provide these assurances. However, an integrated approach that combines: (1) seamless integration of offline and online verification (to deal with inherent limitations of verification), with (2) support for runtime evolution of the system (to deal with new or changing goals) is lacking. In this paper, we outline a new approach named Active FORmal Models of Self-adaptation (ActivFORMS) that aims to deal with these challenges. In ActivFORMS, the formal models of the managing system are directly deployed and executed to realize self-adaptation, guaranteeing the verified properties. Having the formal models readily available at runtime paves the way for: (1) incremental verification during system execution, and (2) runtime evolution of the self-adaptive system. Experiences with a robotic system show promising results.