An autonomic software system is capable of adjusting its behavior at runtime in response to changes in the system, its requirements, or the environment in which it executes. Autonomic capabilities are sought-after to automate the management of software in many computing domains, including service-oriented, mobile, cyber-physical and ubiquitous settings. While the benefits of such software are plenty, the development of it has shown to be much more challenging than the traditional software. 

In this talk, I will first provide an introduction to this area of research, followed by an overview of my contributions. Afterwards, I will delve into the details of a particular engineering framework developed in my research group, called FeatUre-oriented Self-adaptatION (FUSION). It brings about two innovations: (1) a feature-oriented approach for representing the adaptation choices that are deemed practical by the engineers, and (2) an online learning-based approach for automatically acquiring the knowledge to troubleshoot and manage a software system. I will present an empirical evaluation of FUSION in the context of a case study. Results demonstrate FUSION’s ability to accurately learn the changing dynamics of the system, while achieving efficient analysis and adaptation. I will conclude the talk with an outline of my future research agenda.