The complexity of embedded systems can partly be handled by models and domain-specific languages (DSLs) like Matlab / Simulink. If we want to apply such techniques to families of similar systems, we have to describe their variability, i.e., commonalities and differences between the similar systems. Here, approaches from Software Product Lines (SPL) and variability modeling can be helpful. In this paper, we discuss three challenges which arise in this context: (1) We have to integrate mechanisms for describing variability into the DSL. (2) To efficiently derive products, we require techniques and tool-support that allow us to configure a particular product and resolve variability in the DSL. (3) When resolving variability, we have to take into account dependencies between elements, e.g., when removing Simulink blocks we have to remove the signals between these blocks as well. The approach presented here uses higher-order transformations (HOT), which derive the variability mechanisms (as a generated model transformation) from the meta-model of a DSL. © Springer-Verlag Berlin Heidelberg 2010.
CITATION STYLE
Botterweck, G., Polzer, A., & Kowalewski, S. (2010). Using higher-order transformations to derive variability mechanism for embedded systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6002 LNCS, pp. 68–82). https://doi.org/10.1007/978-3-642-12261-3_8
Mendeley helps you to discover research relevant for your work.