Fault diagnosis in scan-based BIST using both time and space information

A new technique for diagnosis in a scan-based BIST environment is presented. It allows non-adaptive identification of both the scan cells that capture errors (space information) as well as a subset of the failing test vectors (time information). Having both space and time information allows a faster and more precise diagnosis. Previous techniques for identifying the failing test vectors during BIST have been limited in the multiplicity of errors that can be handled and/or require a very large hardware overhead. The proposed approach, however, uses only two cycling registers at the output of the scan chain to accurately identify a subset of the failing BIST test vectors. This is accomplished using some novel pruning techniques that efficiently extract information from the signatures of the cycling registers. While not all the failing BIST test vectors can be identified, results indicate that a significant number of them can be. This additional information can save a lot of time in failure analysis.