Test issues in application-specific digital filter data paths are investiga
ted. It is found that such designs can contain hundreds of redundant faults
, making it difficult to accurately determine fault coverage. Since these r
edundant faults tend to appear in the same general location as test-resista
nt faults, the presence of many redundant faults can hide significant untes
ted faults despite high overall test coverage. Classes of redundant faults
that arise in digital filter datapaths are described, and we propose a suit
e of techniques for identifying and eliminating the most common redundancie
s based on arithmetic optimization, The approach is suitable as a front end
to more accurate fault simulation, or can be used in the design process to
eliminate redundant logic, The approach is validated as a tool for develop
ing very high-coverage built-in self-test circuits, showing that 100% fault
coverage can be achieved in 24k-gate filters with as little as 1% area ove
rhead. When used as a datapath optimization technique, the average area red
uction over 15 designs was 8.9%, compared with moderately optimized designs
. As a front-end to fault simulation, the approach yielded a 97.9% average
reduction in the number of undetected faults across the 15 designs.