Automatic Selection of Internal Observation Signals for Design Verification
Tao Lv, Huawei Li, Xiaowei Li · 2009
As the design complexity increases dramatically, results of functional simulation are usually checked through only a part of signals during design verification. It is important, therefore, to consider the observability of internal signals for effective checking. This paper proposes a static observability analysis method to automatically select internal observation signals, which improves the quality of functional verification. A series of formulas are defined to evaluate observability of internal signals, and an algorithm is proposed to locate the sources of low-observability. Such sources, rather than general hard-to-observe signals, are desirable internal observation signals. Experimental results indicate that signals selected by this method can improve the observability of designs more than those randomly selected from hard-to-observe signals.