A Testing Framework for Model Transformations

نویسندگان

  • Yuehua Lin
  • Jing Zhang
  • Jeff Gray
چکیده

As models and model transformations are elevated to first-class artifacts within the software development process, there is an increasing need to provide support for techniques and methodologies that are currently missing in modeling practice, but provided readily in other stages of the development lifecycle. Within a model transformation infrastructure, it is vital to provide foundational support for validation and verification of model transformations by investigating and constructing a testing framework focused on models, rather than source code. This paper presents a framework for testing model transformations that is based on the concepts of model difference and mapping. This framework is integrated with an existing model transformation engine to provide facilities for construction of test cases, execution of test cases, comparison of the output model with the expected model, and visualization of test results. A case study in model transformation testing is presented to illustrate the feasibility of the framework.

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تاریخ انتشار 2004