Abstract

Test points are inserted into integrated circuits to increase fault coverage especially in logic built-in self-test schemes. Commercial tools have been developed over the past decade to insert test points in circuits under test, but they are often inefficient and incur unacceptably large area overhead. Our analysis shows that many test points have little or no impact on test coverage. Furthermore, depending on where test points are inserted, they can create a significant area overhead unnecessarily. Therefore, we propose a novel timing-aware framework to evaluate test points’ impact on a design, rank them based on their efficiency, and obtain an optimal configuration of the most efficient test points accurately and rapidly. Specifically, the proposed framework considers not only individual test coverage improvement but also area penalty, path timing, and region in which each test point is inserted. Within this framework, we have two metrics, namely, efficient test point insertion (ETPI) and test point removal estimation (TPRE). The ETPI metric is developed to remove the most inefficient test points inserted in the circuit by commercial tools, thereby minimizing area penalty with very limited test coverage loss. The TPRE metric is introduced to estimate area overhead and test coverage for designs with different percentages (number) of test points removed without the actual insertion of test points and without the need for lengthy circuit simulation, thereby quickly selecting the most effective test point removal scheme and saving significant amount of processing time especially for large circuits. Experimental results, collected by applying the metrics to NXP Semiconductors circuits and academic benchmark circuits, indicate that ETPI can reduce area overhead by up to 95% with test coverage loss as low as 0.57%. In addition, results by applying the TPRE metric indicate that the difference between estimation and actual simulation/synthesis results for area overhead is less than 0.20% for most cases, and the difference between them for test coverage is less than 1% for most cases.

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