Scalable Compact Test Pattern Generation for Path Delay Faults Based on Functions

A recent decision diagram-based algorithm was able to generate test patterns for each sensitizable path delay fault. Although scalable this approach results to prohibitively long test sets. This paper presents a novel technique to intelligently select paths for compaction. It guarantees optimal compaction subject to the order of processing faults. The compaction rate is superior to any published method, even for the small benchmarks where enumerative compaction methods have been proposed. Experimental results on the publicly available benchmarks demonstrate the scalability of the proposed method.