More than a decade ago, the research topic models@ run. time was coined. Since then, the
research area has received increasing attention. Given the prolific results during these …

A self-adaptive software system modifies its behavior at runtime in response to changes
within the system or in its execution environment. The fulfillment of the system requirements …

We propose an approach to learn image representations that consist of disentangled factors
of variation without exploiting any manual labeling or data domain knowledge. A factor of …

The pervasiveness and growing complexity of software systems are challenging software
engineering to design systems that can adapt their behavior to withstand unpredictable …

Most approaches for adaptive systems rely on models, particularly behaviour or architecture
models, which describe the system and the environment in which it operates. One of the …

Abstract [Context/Motivation] Different modeling techniques have been used to model
requirements and decision-making of self-adaptive systems (SASs). Specifically, goal …

Uncertainty can be defined as the difference between information that is represented in an
executing system and the information that is both measurable and available about the …

Bayesian decision theory is increasingly applied to support decision-making processes
under environmental variability and uncertainty. Researchers from application areas like …

Abstract Self-Adaptive Systems modify their behavior at run-time in response to changing
environmental conditions. For these systems, Non-Functional Requirements play an …

Context Latent uncertainty in the context of software-intensive systems (eg, Cyber-Physical
Systems (CPSs)) demands explicit attention right from the start of development. Use case …