Complete and accurate clone detection in graph-based models

Model-Driven Engineering (MDE) has become an important development framework for many large-scale software. Previous research has reported that as in traditional code-based development, cloning also occurs in MDE. However, there has been little work on clone detection in models with the limitations on detection precision and completeness. This paper presents ModelCD, a novel clone detection tool for Matlab/Simulink models, that is able to efficiently and accurately detect both exactly matched and approximate model clones. The core of ModelCD is two novel graph-based clone detection algorithms that are able to systematically and incrementally discover clones with a high degree of completeness, accuracy, and scalability. We have conducted an empirical evaluation with various experimental studies on many real-world systems to demonstrate the usefulness of our approach and to compare the performance of ModelCD with existing tools.