Reply To: Merging coverage databases

[Mikael]

So I can’t help from elaborate on this subject.
Why are we using constrained random data generation?

*  Because we want to write less tests
*  Run the same test with multiple seeds and hit different things
* We want to use random data (and random order of data)

So functional coverage is there because that is the only way of knowing what you really have tested.

In any, but the most simple cases, reaching 100 % coverage is not easily done. 
E.g. if we talk about for example sequential scenarios (ADD followed by a SUB followed by a MULT) it almost immediately becomes nessecary to run multiple tests and merge the data.
Many times you need to limit your goals to what is practically reachable and target your corner cases.

Also to make this even more interesting. In the end we only want to run the simulations with specific seeds that actually contribute to coverage. This means that we also need to be able to do test associated merging and ranking of simulations.
 
So doing as you say:
<i>With OSVVM, within each testcase, we create a targeted functional coverage model for what we want to see during that test.  Intelligent Coverage drives a test to coverage closure by only randomly selecting items among the coverage holes.  </i>

This means that you need to write a lot more tests while the whole idea with CR methodology is
to rerun the same test(s) with different seeds and not spend time writing a lot of tests. I.e. you spend your time writing coverage goals instead of tests.  Your way, you are writing coverage goals AND more tests.

BR
Mikael Andersson

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Mikael Andersson
European Application Engineer

Digital Design & Verification Solutions

Mentor Graphics (Scandinavia) AB
Kista Science Tower
S-164 51 Kista, Sweden
mailto:Mikael_Andersson@mentor.com
Mobile: +46 (0)709 329516
Office: +46 (0)8 6329516
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