A Quality Model for Conceptual Models of MDD Environments

Abstract

In Model-Driven Development (MDD) processes, models are key artifacts that are used as input for code generation. Therefore, it is very important to evaluate the quality of these input models in order to obtain high-quality software products. The detection of defects is a promising technique to evaluate software quality, which is emerging as a suitable alternative for MDD processes. The detection of defects in conceptual models is usually manually performed. However, since current MDD standards and technologies allow both the specification of metamodels to represent conceptual models and the implementation of model transformations to automate the generation of final software products, it is possible to automate defect detection from the defined conceptual models. This paper presents a quality model that not only encapsulates defect types that are related to conceptual models but also takes advantage of current standards in order to automate defect detection in MDD environments.