Tuning Stochastic Space Compaction to Faster-than-at-Speed Test

摘要

Small delay faults on short paths may be undetectable even during at-speed test. Faster-than-at-speed test (FAST) targets these hidden delay faults by overclocking the circuit, typically using several different test frequencies. Due to the shorter clock periods, the output values on long paths may not stabilize fast enough, and the resulting unknown values (X-values) aggravate test response compaction. As the number and the distribution of X-values vary with the test frequency, X-handling for FAST must be very flexible. Most of the state-of-the-art approaches for X-tolerant test response compaction are not designed for varying X-profiles. Yet, the stochastic compactor by Mitra et al. offers an easily programmable solution, as the com?paction logic is controlled by weighted pseudo-random signals. An optimal setup, however, cannot be guaranteed in a FAST scenario. To better adapt the scheme to FAST, the compactor is partitioned into several smaller compactors and the scan outputs are properly assigned to compactor inputs. Finding the best setup then corresponds to a clustering problem, for which several algorithms are presented. Experimental results show that the number of X-values at the compactor outputs can be significantly reduced while maintaining the fault efficiency.