Modular and Incremental Global Model Management with Extended Generalized Discrimination Networks

TL;DR

This paper introduces an extension to Generalized Discrimination Networks (GDNs) for modular and incremental global model management, enabling efficient processing of large-scale, interrelated models with side-effect operations.

Contribution

It extends GDNs to support operations with side effects and provides incremental algorithms and a prototype, enhancing global model management capabilities.

Findings

Prototype implementation demonstrates practical applicability.

Experimental results show improved scalability.

Approach effectively manages complex model networks.

Abstract

Complex projects developed under the paradigm of model-driven engineering nowadays often involve several interrelated models, which are automatically processed via a multitude of model operations. Modular and incremental construction and execution of such networks of models and model operations are required to accommodate efficient development with potentially large-scale models. The underlying problem is also called Global Model Management. In this report, we propose an approach to modular and incremental Global Model Management via an extension to the existing technique of Generalized Discrimination Networks (GDNs). In addition to further generalizing the notion of query operations employed in GDNs, we adapt the previously query-only mechanism to operations with side effects to integrate model transformation and model synchronization. We provide incremental algorithms for the execution of the resulting extended Generalized Discrimination Networks (eGDNs), as well as a prototypical implementation for a number of example eGDN operations. Based on this prototypical implementation, we experiment with an application scenario from the software development domain to empirically evaluate our approach with respect to scalability and conceptually demonstrate its applicability in a typical scenario. Initial results confirm that the presented approach can indeed be employed to realize efficient Global Model Management in the considered scenario.