Applying the Knowledge Stored in Systems Models to Derve Validation Tools and Environments

It is frequent that test tools are basically independent from the application domain. This is usually the case for languages as well. This reflection becomes particularly relevant for validation tools, since the validation process is closely related to requirements. Therefore, test engineers must work at a much lower level of abstraction than that of the system domain. The problem is especially relevant when dealing with complex systems, in which hardware and software are closely related, such as ambient intelligence systems, automotive, power plants, telecommunication and autonomic systems in general. The authors of this paper claim that validation tools can and will be domain specific in the future. For this reason, they will have to include knowledge defined in the system requirements. As explained within this paper, this knowledge can be incorporated into the validation tools with limited involvement from the test engineer. These domain specific-tools will make the task easier for test engineers. This paper analyzes the different kinds of knowledge involved in domain-specific validation tools, specifically acceptance testing tools. The knowledge is expressed in terms of requirements and models. This paper also presents a model driven engineering approach to derive validation tools and environments from system models. This approach uses model transformations. Derivation can be performed in either a semiautomatic or fully automatic way depending on the system characteristics. Through these approaches, software and systems engineers can access to domain-specific validation tools during the early stages of the system life cycle.