Abstract
Physical products come in many variants, and so does the software embedded in them. The software embedded in a product variant usually has to be optimized to fit its limited memory and computing power. Generative programming is well suited for developing embedded software since it allows us to automatically produce variants of embedded software optimized for specific products. This paper reports on our experience in applying generative programming in the embedded domain. We propose an extended feature modeling notation, discuss tool support for feature modeling, describe a domain-independent system configuration editor, and comment on the applicability of static configuration in the area of embedded systems.
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Czarnecki, K., Bednasch, T., Unger, P., Eisenecker, U. (2002). Generative Programming for Embedded Software: An Industrial Experience Report. 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_10
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DOI: https://doi.org/10.1007/3-540-45821-2_10
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