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AUTOMATED TEST CASE GENERATION FOR DEEP NEURAL NETWORKS AND OTHER MODEL-BASED ARTIFICIAL INTELLIGENCE SYSTEMS
AUTOMATED TEST CASE GENERATION FOR DEEP NEURAL NETWORKS AND OTHER MODEL-BASED ARTIFICIAL INTELLIGENCE SYSTEMS
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机译:深度神经网络和其他基于模型的人工智能系统的自动测试案生成
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摘要
Methods, systems and computer program products for automated test case generation are provided herein. A computer-implemented method includes selecting sample input data as a test case for a system under test, executing the test case on the system under test to obtain a result, and applying the result to a local explainer function to obtain at least a portion of a corresponding decision tree. The method further includes determining at least one path constraint from the decision tree, solving the path constraint to obtain a solution, and generating at least one other test case for the system under test based at least in part on the solution of the path constraint. The steps of the method are illustratively repeated in each of one or more additional iterations until at least one designated stopping criterion is met. The resulting test cases form a test suite for testing of a deep neural network (DNN) or other system.
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