Decomposing Models Through Dependency Graphs

In Model-Driven Engineering (MDE), models are the primary artifacts of software development life cycles. Being an abstraction of the real systems, models are generally believed to be less complex and better suited for developing, comprehending, communicating, and analyzing systems. However, such an advantage is decreasing with the tendency of models themselves getting more and more complex. In this paper we propose a model decomposition technique for reducing model size and consequently complexity by exploiting the notion of dependency graphs. Compared to its predecessor, this new model decomposition technique is more effective in terms of both the number of derived sub-models (more), the size of sub-models (finer), and the quality of sub-models (better). We demonstrate the improved effectiveness by applying both the previous and the new algorithm to a common example and comparing the results.