Multi-view modeling allows a developer to describe a software system from multiple points of view, e.g. structural and behavioral, using different modeling notations. Aspectoriented modeling techniques have been proposed to address the scalability problem within individual modeling notations. This paper presents RAM, an aspect-oriented modeling approach that provides scalable multi-view modeling. RAM allows the modeler to define stand-alone reusable aspect models using 3 modeling notations. The aspect models support the modeling of structure (using UML class diagrams) and behavior (using UML state and sequence diagrams). RAM supports aspect dependency chains, which allows an aspect providing complex functionality to reuse the functionality provided by other aspects. The RAM weaver can create woven views of the composed model for debugging, simulation or code generation purpose, as well as perform consistency checks during the weaving and on the woven model to detect inconsistencies of the composition.
In REF , the authors propose Ram, an aspect-oriented modeling approach that provides multi-view modeling, covering structural, state-based, and scenario-based models.
Aspect-oriented multi-view modeling
AOSD '09
Computer Science