Generative Programming for Embedded Software: An Industrial Experience Report

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.