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High-Level Models for Transformation-Oriented Design of Hardware and Embedded Systems

DAMASEVICIUS, R. See more information about DAMASEVICIUS, R. on SCOPUS See more information about DAMASEVICIUS, R. on IEEExplore See more information about DAMASEVICIUS, R. on Web of Science, STUIKYS, V. See more information about STUIKYS, V. on SCOPUS See more information about STUIKYS, V. on SCOPUS See more information about STUIKYS, V. on Web of Science
 
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Download PDF pdficon (664 KB) | Citation | Downloads: 862 | Views: 3,142

Author keywords
design automation, transformation, hardware and embedded system design

References keywords
design(37), model(29), software(22), systems(17), embedded(13), system(12), driven(12), dama(11), tuikys(10), development(9)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2008-06-02
Volume 8, Issue 2, Year 2008, On page(s): 86 - 94
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2008.02016
Web of Science Accession Number: 000264815000016
SCOPUS ID: 77954751851

Abstract
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Evolution of design methodologies follows a common trail: technology scaling leads to growing design complexity and rising abstraction level in the domain. Introduction of new (higher) abstraction levels emphasizes the importance of reuse and transformations. The design process can be seen as a sequence of high-level transformations from the higher-level specification to the lower-level one. We analyze high-level modeling and metaprogramming techniques for supporting transformations based on domain variability models. Next, we present a reuse evolution model for domain component design at a higher abstraction level to support the transformation-oriented approaches. Finally, high-level modeling techniques (UML-domain language metamodels for domain code generation, parameterized UML classes for template metaprogramming, feature models for explicit representation of variability) for specification of transformations and metaprograms are analyzed.


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References Weight

Web of Science® Citations for all references: 115 TCR
SCOPUS® Citations for all references: 321 TCR

Web of Science® Average Citations per reference: 2 ACR
SCOPUS® Average Citations per reference: 5 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

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