Divide and Compact - Stochastic Space Compaction for Faster-than-at-Speed Test

摘要

With shrinking feature sizes detecting small delay faults is getting more and more important. But not all small delay faults are detectable during at-speed test. By overclocking the circuit with several different test frequencies faster-than-at-speed test (FAST) is able to detect these hidden delay faults. If the clock frequency is increased, some outputs of the circuit may not have stabilized yet, and these outputs have to be considered as unknown (X-values). These X-values impede the test response compaction. In addition, the number and distribution of the X-values vary with the clock frequency, and thus a very flexible X-handling is needed for FAST. Most of the state-of-the-art solutions are not designed for these varying X-profiles. Yet, the stochastic compactor by Mitra et al. can be adjusted to changing environments. It is easily programmable because it is controlled by weighted pseudo-random signals. But an optimal setup cannot be guaranteed in a FAST scenario. By partitioning the compactor into several smaller ones and a proper mapping of the scan outputs to the compactor inputs, the compactor can be better adapted to the varying X-profiles. Finding the best setup can be formulated as a set partitioning problem. To solve this problem, several algorithms are presented. Experimental results show that independent from the scan chain configuration, the number of X-values can be reduced significantly while the fault efficiency can be maintained. Additionally, it is shown that X-reduction and fault efficiency can be adapted to user-defined goals.