Test-Quality Optimization for Variable $n$ -Detections of Transition Faults

Aggressive technology scaling in modern chips resulted in complicated faulty timing behaviors, which necessitate undesirable long development cycle and high test volumes to ensure product quality. To reduce the test time, cost-effective and timing-efficient test selection algorithms are used to choose optimal test inputs from a large-volume test set. In this paper, we define an approximate longest sensitized path (ALSP) metric to derive the longest sensitized path for all transition faults (TFs) from the detectability of TFs with very low computational complexity. With the ALSP metric, a general public utilities-based parallel test selection method is proposed to choose a small test set with high delay test quality from the timing-unaware n-detection test set. Our results demonstrate the comparison with a commercial automatic test pattern generation tool and a previous timing-aware test selection method targeting small delay defects, and confirm that our test selection algorithm can achieve better delay test coverage and higher n -detection fault coverage with steeper fault coverage curves of ordered patterns, for the same pattern count.