Hierarchical test pattern generation based on high-level primitives

It is demonstrated that the exploitation of high-level primitives (HLPs) and, in particular, of the knowledge concerning their function in ATPG (automatic test pattern generation) leads to significant improvements in implication, unique sensitization, and multiple backtrace. Motivated by this observation and the necessity of covering all faults inside HLPs, the authors present the extension of the ATPG system SOCRATES to hierarchical test pattern generation, which is based upon HLPs and the strategy of dynamically expanding the HLPs to their gate-level realization, at most one at a time. Experimental results have substantiated that the proposed approach performs significantly better in terms of CPU time, elapsed time, fault coverage, and memory requirements than a gate-level ATPG algorithm. It is expected that the extended SOCRATES algorithm will be capable of coping with circuits consisting of 100000 gates and more within reasonable times, even in a workstation environment