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Diagnostic Test Set Minimization and Full-Response Fault Dictionary

机译:诊断测试集最小化和全响应故障字典

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摘要

We minimize a given test set without loss of diagnostic resolution in full-response fault dictionary. An integer linear program (ILP), formulated from fault simulation data, provides ultimate reduction of test vectors while preserving fault coverage and pair-wise distinguishability of faults. The complexity of the ILP is made manageable by two innovations. First, we define a generalized independence relation between pairs of faults to reduce the number of fault pairs that need to be distinguished. This significantly reduces the number of ILP constraints. Second, we propose a two-phase ILP approach. In the first phase, using an existing procedure, we select a minimal detection test set. In the second phase, additional tests are selected for the undiagnosed faults using a newly formulated diagnostic ILP. The overall minimized test set may be only slightly longer than a one-step ILP optimization, but has advantages of reducing the minimization problem complexity and the test time required by the minimized tests. Benchmark results show potential for significantly smaller diagnostic test sets.
机译:我们将给定的测试集最小化,而不会损失全响应故障字典中的诊断分辨率。由故障仿真数据制定的整数线性程序(ILP)可最大程度地减少测试向量,同时保留故障覆盖率和故障的成对区分性。两项创新使ILP的复杂性得以管理。首先,我们定义了故障对之间的广义独立关系,以减少需要区分的故障对的数量。这大大减少了ILP约束的数量。其次,我们提出了两阶段的ILP方法。在第一阶段,使用现有程序,我们选择最小检测测试集。在第二阶段中,使用新制定的诊断性ILP为未诊断的故障选择其他测试。总体最小化的测试集可能仅比一步ILP优化稍长,但是具有减少最小化问题的复杂性和最小化测试所需的测试时间的优势。基准测试结果显示出显着减少诊断测试集的潜力。

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