Combining different techniques for sequential automated test pattern genera
tion (ATPG) can help overcome their respective limits and exploit their adv
antages. In this paper, a hybrid technique resulting from mixing topologic
and symbolic approaches to the sequential ATPG problem is presented. Macros
are first identified within the circuit (possibly resorting to RT-level kn
owledge of circuit architecture). Information about macro behavior is then
computed and efficiently stored resorting to symbolic techniques. A topolog
ical tool exploits this information during the ATPG process to speed-up the
propagation task and to identify early unsuccessful choices, Experimental
results are reported, demonstrating that the method is able to improve the
efficiency of a topological ATPG in terms of required CPU time and attained
fault coverage, especially on medium-sized control-dominated circuits.