Test Pattern Generation and Critical Path Selection in the Presence of Statistical Delays

摘要

The statistical delay of a path is traditionally modeled as a Gaussian random variable assuming that the path is always sensitized by a test pattern. Its sensitization in various circuit instances varies among its test patterns and the pattern induced delay is non-Gaussian. It is modeled using probability mass functions (PMFs). This article presents an automatic test pattern generation (ATPG) method, where multiple uncorrelated test patterns per path improve its defect coverage (DC). The impact of the ATPG process is evaluated by comparing to traditional methods. It is also shown that the presented ATPG is useful in selecting critical paths.