Regression Test Selection Model using Decomposition Slicing

Amir Ngah, Malcolm Munro, and Keith Gallagher


regression test selection, decomposition slicing, exclusive model


Software systems change and evolve over time. Each time a system is changed regression tests have to be run to validate these changes. The aim of this research is to significantly reduce the number of test cases that need to be run after system changes have been made. Decomposition slicing provides a technique that is capable of identifying the unchanged parts of a system. A model based on decomposition slicing has been developed. The validity of the model is explored through the application of an example. Application of this model has shown that significant reductions in the number of test cases can be achieved. The example have limited themselves to relatively small programs and the next step is to apply the model to larger systems with more complex changes to ascertain if the method scales. While some parts of the model have been automated, tools will be required when carrying out the larger case studies.

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