IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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Most of the recently discussed and commercially introduced teststimulus data compression techniques are based on low care bitdensities found in typical scan testvectors. Data volume and testtimes are reduced primarily by compressing the don't-care bitinformation. The original care bit density, hence, dominates thetheoretical compression limits. Further compression can be achievedby focusing on opportunities to compress care bit information inaddition to the don't-care bit information. This paper discusses ata conceptual level how data compression based on test cubeclustering effects, as used in Weighted Random Pattern methods,could be combined with care bit oriented methods to achievemulti-level test stimulus compression.