Deep learning has become the method of choice to tackle real-world problems in different
domains, partly because of its ability to learn from data and achieve impressive performance …

Context: Self-adaptive systems have been studied in software engineering over the past few
decades attempting to address challenges within the field. There is a continuous significant …

Recent advances in deep learning have led to the development of accurate and efficient
models for various computer vision applications such as classification, segmentation, and …

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

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 …

Self-adaptive systems (SASs) are designed to handle changes and uncertainties through a
feedback loop with four core functionalities: monitoring, analyzing, planning, and execution …

This article addresses the need of applying testing activities with the purpose of checking the
consistency and the correctness of distributed and dynamically adaptable systems whose …

Field testing refers to testing techniques that operate in the field to reveal those faults that
escape in-house testing. Field testing techniques are becoming increasingly popular with …

Context: Championed by IBM's vision of autonomic computing paper in 2003, the autonomic
computing research field has seen increased research activity over the last 20 years …

In this dissertation we report on our main research contributions dealing with Model-Based
Testing of Dynamic and Distributed Real-Time Systems, performed during the last ten years …