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Generative Programming for Embedded Systems

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2487))

Abstract

Embedded systems represent fundamentally new challenges for software design, which render conventional approaches to software composition ineffective. Starting with the unique challenges of building embedded systems, this paper discusses key issues of model-based technology for embedded systems. The discussion uses Model-Integrated Computing (MIC) as an example for model-based software development. In MIC, domain-specific, multiple view models are used in all phases of the development process. Models explicitly represent the embedded software and the environment it operates in, and capture the requirements of the application, simultaneously. Models are descriptive, in the sense that they allow the formal analysis, verification and validation of the embedded system at design time. Models are also generative, in the sense that they carry enough information for automatically generating embedded systems from them using the techniques of program generators.

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Sztipanovits, J., Karsai, G. (2002). Generative Programming for Embedded Systems. In: Batory, D., Consel, C., Taha, W. (eds) Generative Programming and Component Engineering. GPCE 2002. Lecture Notes in Computer Science, vol 2487. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45821-2_2

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  • DOI: https://doi.org/10.1007/3-540-45821-2_2

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44284-4

  • Online ISBN: 978-3-540-45821-0

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