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Test case Generation from Cause-Effect Graph based on Model Transformation

Authors
Son, Hyun SeungKim, R. Young ChulPark, Young B.
Issue Date
2014
Publisher
IEEE
Keywords
Model Transformation; Cause-Effect Graph; Test case Generation; Testing; Metamodel
Citation
2014 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND APPLICATIONS (ICISA)
Journal Title
2014 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND APPLICATIONS (ICISA)
URI
https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/29565
ISSN
2162-9048
Abstract
In software testing, cause-effect graph assures coverage criteria of 100% functional requirements with minimum test case. The existing test case generation from cause-effect graph implements the algorithmic approach. It has disadvantages to modify the entire program if the input model is different. In contrast, model transformation approach can flexibly implement with even a different input models. In the future, we need to study the method of automatic generation of test cases from UML Diagram. It is possible to generate the test case when mapping between cause-effect graph and UML diagram. In this paper, as a first research step, we propose the method to generate test cases from cause-effect graph based on model transformation. To implement the proposed method, we write the rules of model transformation with ATLAS Transformation Language (ATL), and execute the rules in development environment of Eclipse. The implemented tool of the proposed method can be easily extended by rewriting with the mapping rule between cause-effect graph and UML diagram. We just define the relationship between each models to generate the test case.
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