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A Hybrid Regression Test Selection Technique for Object-Oriented Programs

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Executive Summary

The authors propose a regression test selection technique that is based on analysis of both the source code of an object-oriented program as well as the UML state machine models of the affected classes. They first construct a dependency graph model of the original program from the source code. When the program is suitably modified, the constructed model is updated to reflect the changes. Their model in addition to capturing control and data dependencies represents the dependencies arising from object-relations. To find the model elements affected due to a program change, they construct a forward slice of the constructed graph model, where each changed model element is used as a slicing criterion.

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