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Evolvability, the ability to respond effectively to change, represents a major challenge to today's high-end embedded systems, such as those developed in the medical domain by Philips Healthcare. These systems are typically developed by multi-disciplinary teams, located around the world, and are in constant need of upgrading to provide new advanced features, to deal with obsolescence, and to exploit emerging enabling technologies. Despite the importance of evolvability for these types of systems, the field has received scant attention from the scientific and engineering communities. Views on Evolvability of Embedded Systems focuses on the topic of evolvability of embedded systems from an applied scientific perspective. In particular, the book describes results from the Darwin project that researched evolvability in the context of Magnetic Resonance Imaging (MRI) systems. This project applied the Industry-as-Laboratory paradigm, in which industry and academia join forces to ensure continuous knowledge and technology transfer during the project’s lifetime. The Darwin project was a collaboration between the Embedded Systems Institute, the MRI business unit of Philips Healthcare, Philips Research, and five Dutch universities. Evolvability was addressed from a system engineering perspective by a number of researchers from different disciplines such as software-, electrical- and mechanical engineering, with a clear focus on economic decision making. The research focused on four areas: data mining, reference architectures, mechanisms and patterns for evolvability, in particular visualization & modelling, and economic decision making. Views on Evolvability of Embedded Systems is targeted at both researchers and practitioners; they will not only find a state-of-the-art overview on evolvability research, but also guidelines to make systems more evolvable and new industrially-validated techniques to improve the evolvability of embedded systems.

Embedded computer systems. --- Adaptive computing systems --- Embedded computer systems --- Magnetic resonance imaging --- Engineering & Applied Sciences --- Electrical & Computer Engineering --- Electrical Engineering --- Computer Science --- Adaptive computing systems. --- Magnetic resonance imaging. --- Clinical magnetic resonance imaging --- Diagnostic magnetic resonance imaging --- Functional magnetic resonance imaging --- Imaging, Magnetic resonance --- Medical magnetic resonance imaging --- MR imaging --- MRI (Magnetic resonance imaging) --- NMR imaging --- Nuclear magnetic resonance --- Nuclear magnetic resonance imaging --- Embedded systems (Computer systems) --- Adaptive computing --- Configurable computing systems --- Reconfigurable computing systems --- Diagnostic use --- Engineering. --- Special purpose computers. --- Electronic circuits. --- Circuits and Systems. --- Special Purpose and Application-Based Systems. --- Electron-tube circuits --- Electric circuits --- Electron tubes --- Electronics --- Special purpose computers --- Computers --- Construction --- Industrial arts --- Technology --- Cross-sectional imaging --- Diagnostic imaging --- Computer systems --- Architecture Analysis and Design Language --- Systems engineering. --- Software engineering. --- Computer software engineering --- Engineering --- Engineering systems --- System engineering --- Industrial engineering --- System analysis --- Design and construction

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Adaptive computing systems --- Embedded computer systems --- Magnetic resonance imaging