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 …

Self-reconfiguration enables a dynamically adaptive system (DAS) to satisfy requirements
even as detrimental system and environmental conditions arise. A DAS, especially one …

Modern software systems are often characterized by uncertainty and changes in the
environment in which they are embedded. Hence, they must be designed as adaptive …

Self-adaptive systems (SAS) may be subjected to conditions for which they were not
explicitly designed. For those high-assurance SAS applications that must deliver critical …

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 …

Since deep learning systems do not generalize well when training data is incomplete and
missing coverage of corner cases, it is difficult to ensure the robustness of safety-critical self …

It is challenging to design, develop, and validate a dynamically adaptive system (DAS) that
satisfies requirements, particularly when requirements can change at run time. Testing at …

Self-adaptive applications address environmental dynamics systematically. They can be
faulty and exhibit runtime errors when environmental dynamics are not considered …

Dynamically adaptive systems (DAS) must cope with system and environmental conditions
that may not have been fully understood or anticipated during development. RELAX is a …

Data-driven Learning-enabled Systems are limited by the quality of available training data,
particularly when trained offline. For systems that must operate in real-world environments …