Discovery the Quality of UML Models Through an Exploration of Dataset in Practice

Within Model-Driven Engineering (MDE) software development, models are considered as central artifacts. Thus, determining and correcting models quality issues occurring in the design phase is essential to ensure the success of the outcome product. Design smell is a kind of quality issue that indicates the weaknesses or drawbacks in the design (models) that might negatively affect the software development and maintainability. In this paper, we utilize an intelligent technique to uncover the typical design smells and quality issues of UML (Unified Modeling Language) models. The answer is achieved through an evaluation and analysis of a large dataset of models in practice.