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It is labor-intensive to manually verify the outputs of a large set of tests that are not equipped with test oracles. Test selection helps to reduce this cost by selecting a small subset of tests that are likely to reveal faults. A promising approach is to dynamically mine operational models as potential test oracles and then select tests that violate them. Existing work mines operational models from verified passing tests based on dynamic invariant detection.
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