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This paper argues that regression test optimization problems such as selection and prioritization require multi objective optimization in order to adequately cater for real world regression testing scenarios. The paper presents several examples of costs and values that could be incorporated into such a Multi Objective Regression Test Optimization (MORTO) approach. Regression test optimization includes the two important related problems of selecting a subset of test cases that give maximum cost-value benefit and ordering test cases such that early attainment of this cost-value trade off is achieved. Both selection and prioritization problems have previously been studied as optimization problems, with a long history.
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