Recently, we have been witnessing a rapid increase in the use of machine learning
techniques in self-adaptive systems. Machine learning has been used for a variety of …

Autonomous robotic systems are complex, hybrid, and often safety critical; this makes their
formal specification and verification uniquely challenging. Though commonly used, testing …

A concise and practical introduction to the foundations and engineering principles of self-
adaptation Though it has recently gained significant momentum, the topic of self-adaptation …

Modern software systems are expected to operate under uncertain conditions, without
interruption. Possible causes of uncertainties include changes in the operational …

The goal of this roadmap paper is to summarize the state-of-the-art and identify research
challenges when develo**, deploying and managing self-adaptive software systems …

Self-adaptation is typically realized using a control loop. One prominent approach for
organizing a control loop in self-adaptive systems is by means of four components that are …

Building on concepts drawn from control theory, self-adaptive software handles
environmental and internal uncertainties by dynamically adjusting its architecture and …

Computing systems form the backbone of many areas in our society, from manufacturing to
traffic control, healthcare, and financial systems. When software plays a vital role in the …

Designing software systems that have to deal with dynamic operating conditions, such as
changing availability of resources and faults that are difficult to predict, is complex. A …

One major challenge in self-adaptive systems is to assure the required quality properties.
Formal methods provide the means to rigorously specify and reason about the behaviors of …