Semantics Of Modeling Languages Research Articles

Semantic-element-based Defining Approach for Model Transformation Rules

In model-driven software development, it is a key technology that transform from platform independent models at higher abstract level to platform specific models at a lower level. The approach to create mapping rules is profoundly impacted with the gap between the source model and the target model. By abstractly analyzing the characteristic of syntax and semantics of modeling languages, an approach to define model transformation rules is proposed on the basis of semantic consistency. Firstly, the user must construct an abstract semantic model through an in-depth analysis of target platform. Secondly, the user build mapping relations from source model to target model via abstract target semantic model. This work is based on the idea of elements in source semantic domain being reconstructed in the target semantic domain. The approach can provide an effective support for validating mapping rules between different abstract level models. JavaEE is used as a target of the transformation to interpreting the process to define mapping rules.

Model Mapping Approach Based on Ontology Semantics

The mapping relations between different models are the foundation for model transformation in model-driven software development. On the basis of ontology semantics, model mappings between different levels are classified by using structural semantics of modeling languages. The general definition process for mapping relations is explored, and the principles of structure mapping are proposed subsequently. The approach is further illustrated by the mapping relations from class model of object oriented modeling language to the C programming codes. The application research shows that the approach provides a theoretical guidance for the realization of model mapping, and thus can make an effective support to model-driven software development

An embeddable virtual machine for state space generation

The semantics of modelling languages are not always specified in a precise and formal way, and their rather complex underlying models make it a non-trivial exercise to reuse them in newly developed tools. We report on experiments with a virtual machine-based approach for state space generation. The virtual machine’s (VM) byte-code language is straightforwardly implementable, facilitates reuse and makes it an adequate target for translation of higher-level languages like the SPIN model checker’s Promela, or even C. As added value, it provides efficiently executable operational semantics for modelling languages. Several tools have been built around the VM implementation we developed, to evaluate the benefits of the proposed approach.