Weighted random LFSRs are widely used for reproducing a deterministic test-
set, Large test sets are partitioned into subsets and more than one weight-
sets is necessary, one weight-set per subset. It has been proposed to parti
tion by taking into consideration the Hamming distance between pairs of vec
tors. This paper introduces a systematic approach for partitioning a given
deterministic test-set into subsets so that the reproduction time is minimi
zed. It presents and evaluates properties that each set in the partition mu
st satisfy. Efficient algorithms are also proposed for partitioning the tes
t-set into subsets that satisfy the proposed criteria. Experimental studies
on the ISCAS'85 benchmarks show significant improvement over previous work
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