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    Entwicklung von Methoden zur abstrakten Modellierung von Automotive Systems-on-Chips

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    Author(s)
    Kirchner, Aljoscha
    Language
    German
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    Abstract
    Diese Open-Access-Publikation bietet zu Beginn einen Einblick in die Grundlagen der modellbasierten Systementwicklung. Dabei analysiert die Publikation aktuell bestehende methodische Defizite in der Automotive System-on-Chip (SoC) Entwicklung. Anschließend beschreibt die Publikation, eine neue modellbasierte Entwicklungsmethode, mit deren Hilfe es ermöglicht wird die wachsenden Herausforderungen der Automotive System-on-Chip Entwicklung zu meistern. Um das übergeordnete Ziel der Effizienzsteigerung zu erfüllen, vereint die modellbasierte Entwicklungsmethode fünf etablierte Werkzeuge und passt dabei die Gesamtmethode auf die Anforderungen der Automotive SoC Entwicklung an. Darüber hinaus behandelt die Publikation die Möglichkeiten zur modellgetriebenen Automatisierung in Hardware- wie auch in der Softwareentwicklung. Den Nachweis über den positiven Einfluss der modellbasierten Entwicklungsmethode auf die Effizienz der Automotive SoC Entwicklung erbringt die Publikation anhand einer Interview-Evaluierung in Form einer leitfaden-basierten Befragung von Anwendern aus der Industrie.
    URI
    https://library.oapen.org/handle/20.500.12657/61311
    Keywords
    model driven design; model driven verification; SysML; modellbasierte Systementwicklung; Automotive SoC Entwicklung; Hardware-co-Design
    DOI
    10.1007/978-3-658-38437-1
    ISBN
    9783658384371, 9783658384371
    Publisher
    Springer Nature
    Publisher website
    https://www.springernature.com/gp/products/books
    Publication date and place
    Wiesbaden, 2022
    Imprint
    Springer Vieweg
    Classification
    Mechanical engineering
    Software Engineering
    Automotive technology and trades
    Maths for engineers
    Pages
    184
    Rights
    http://creativecommons.org/licenses/by/4.0/
    • Imported or submitted locally

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    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

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    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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