Expressing the Adaptation Intent as a Sustainability Goal

Abstract

Adaptation and sustainability are two key challenges leading the development of software-systems nowadays. Adaptation denotes the capacity of a system to cope with variations and uncertainties at runtime in order to continue providing its functionalities with certain quality levels, notwithstanding change. But how can adaptation and its intent be expressed at design time so that to analyze its possible impact at runtime over a long period of time? To answer this question we look at adaptation from the sustainability point of view. Sustainability denotes the capacity of a system to both endure and preserve its function over time. We propose an approach which uses decision maps to make sustainability-driven decisions for adaptation in a systematic way. The proposed approach is illustrated through two self-adaptive exemplars as illustrative cases.

EcoMLS: A Self-Adaptation Approach for Architecting Green ML-Enabled Systems

“…Research in this area [14], [22], [23] categorizes self-adaptation into software design approaches (SDA) and system engineering approaches (SEA), focusing on designtime solutions. Recent studies [15], [24] explore enhancing adaptability at runtime, including unsupervised learning and model switching. Yet, these approaches often limit systems to pre-set configurations, as noted by Tundo et al [25].…”