Model query translator: A model-level query approach for large-scale models

Persisting and querying models larger than a few tens of megabytes using XML introduces a significant time and memory footprint overhead to MDD workflows. In this paper, we present an approach that attempts to address this issue using an embedded relational database as an alternative persistence layer for EMF models, and runtime translation of OCL-like expressions for efficiently querying such models. We have performed an empirical study of the approach using a set of large-scale reverse engineered models and queries from the Grabats 2009 Reverse Engineering Contest. Main contribution of this paper is the Model Query Translator, an approach that translates (and executes) at runtime queries from model-level (EOL) to persistence-level (SQL).