Software-based diagnosis for processors

Software-based self-test (SBST) is emerging as a promising technology for enabling at-speed test of high-speed microprocessors using low-cost testers. We explore the fault diagnosis capability of SBST, in which functional information can be used to guide and facilitate the generation of diagnostic tests. By using a large number of carefully constructed diagnostic test programs, the fault universe can be divided into fine-grained partitions, each corresponding to a unique pass/fail pattern. We evaluate the quality of diagnosis by constructing diagnostic-tree-based fault dictionaries. We demonstrate the feasibility of the proposed method by applying it to a processor example. Experimental results show its potential as an effective method for diagnosing larger processors.