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AUTOMATED TEST CASE GENERATION FOR DEEP NEURAL NETWORKS AND OTHER MODEL-BASED ARTIFICIAL INTELLIGENCE SYSTEMS

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

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.
机译:本文提供了用于自动测试案例的方法,系统和计算机程序产品。计算机实现的方法包括选择样本输入数据作为测试的系统的测试用例,在被测系统上执行测试用例以获得结果,并将结果应用于本地解释器功能以获得至少一部分相应的决策树。该方法还包括确定来自决策树的至少一个路径约束,解决路径约束以获得解决方案,并至少部分地基于路径约束的解决方案来生成被测系统的至少一个其他测试用例。该方法的步骤在一个或多个附加迭代中的每一个中的例子中的说明性重复,直到满足至少一个指定的停止标准。由此产生的测试用例形成测试套件,用于测试深神经网络(DNN)或其他系统。

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