The testing of large logic networks with random patterns is examined. Work by previous workers for single faults is extended to a class of multiple fault situations. Not only is the problem of fault detection in the presence of nonmasking multiple faults treated, but the question of distinguishing between them is also examined. It is shown that a test that merely exposes each fault has a high probability of distinguishing between the faults. The relationships between quality, diagnostic resolution, and random pattern test length are developed. The results have application to self-test schemes that use random patterns as stimuli.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Hardware and Architecture
- Computational Theory and Mathematics