TAILIEUCHUNG - Standardized Functional Verification- P16

Standardized Functional Verification- P16:Every manager who brings a design to tape-out or who purchases IP must eventually face these questions. The ability to answer these questions based on quantitative analysis is both vital and yet elusive. In spite of the enormous technical advances made in IC development and verification software, the answers to these questions are still based largely on guesswork and hand waving. | Bug Count as a Function of Complexity 135 Here it is apparent that using this organization s talent and resources a level of Q of 6000 or higher is needed for a lower-risk tape-out. However values in the 4000 to 6000 range might also be acceptable if time-to-market considerations require taking on somewhat higher risk at tape-out. It s also apparent that a value of Q lower than 4000 is quite risky for a tape-out because historically that quantity of exercise has left too many unexposed bugs. Bug Count as a Function of Complexity One potential measure that may have practical value in estimating the number of bugs in a target is to consider the ratio of bugs to complexity. This may be found to be a simple linear relationship or perhaps some other relationship. Nevertheless an organization that has empirical data on bug counts and complexity may be able to make more accurate predictions of expected bug counts for new verification targets and thereby plan more effectively. Considering the example provided in Fig. and adding upper and lower bounds for expected bug count we arrive at Fig. . Fig. . Forecasting lower and upper bounds for bug count 136 Chapter 5 - Normalizing Data In this figure estimates for lower and upper bounds on bug count have been shown and it appears that the tapering off might be misleading. There might actually be more bugs yet to be discovered if the improvements in RTL code quality cannot be accounted for by other means. In our example CRV testing with error imposition hasn t yet begun and there are more bugs associated with that functionality that remains to be discovered. Comparing Size and Complexity If we can determine the size of the functional space why bother trying to convert that precise value to some approximation of complexity itself a thing that is often not well defined even in this book Complexity whatever it is still exists but if measures are instead based on the precise size of the functional space no .

11    7    0
6    7    0
11    4    0
22    6    0