1. Copyright 2008 - Joanne DeGroat, ECE, OSU
Directed Random Test
10/2/08 - Directed Random Test
Copyright Joanne DeGroat, ECE, OSU

2. Copyright 2008 - Joanne DeGroat, ECE, OSU
Lecture overview
Open discussion of Verification Plan on Project A
Verification Plans are living documents ???
Generation of Random Stimulus
Directed Random Tests
An Example
10/2/08 - Directed Random Test
Copyright Joanne DeGroat, ECE, OSU

3. Generation of Random Stimulus
“Random stimulus is created by a random generator that can be constrained according to the verification plan.”
Often used for automatic generation of test stimulus.
And easy way to generate many test cases (transactions) easily.
10/2/08 - Directed Random Test
Copyright Joanne DeGroat, ECE, OSU

4. Totally Random vs Constrained Random
Consider the Floating Point Adder
If the 32 bits are randomly generated
Most likely a normalized number (probability very high)
Occurrences of NaN, +/- Inif, and 0 will be very minimal – some may not even occur over several thousand vectors
Constrain the random generation so that all cases are adequately covered.
10/2/08 - Directed Random Test
Copyright Joanne DeGroat, ECE, OSU

5. Testing the Floating Point Adder
Step 1 – have adequate test of each class +/- each other class
Nan and each of
+/- Inifity
+/- 0
+/- Normalized number
+/- Denormalized number
For the case of normalized and denormalized must have adequate number of case to insure conficence
10/2/08 - Directed Random Test
Copyright Joanne DeGroat, ECE, OSU

6. Copyright 2008 - Joanne DeGroat, ECE, OSU
Continuing the tests
For +/- Inifinity
+/- 0
+/- Normalized numbers
+/- Denormalized
For +/- 0
As there + and – representations must do the tests for both and across an adequate number of vectors for each case to insure confidence
10/2/08 - Directed Random Test
Copyright Joanne DeGroat, ECE, OSU

7. Copyright 2008 - Joanne DeGroat, ECE, OSU
The real work
Special cases covered – Nan, Inif, and 0 are specific formats and limited to just 6 vectors
Normalized and denormalized vectors make up the rest of the 264 vector space with normalized number making up the bulk of that space.
10/2/08 - Directed Random Test
Copyright Joanne DeGroat, ECE, OSU

8. Specific tests for these
Special cases that you want to test for – and you want more than testing one instance
You add two large normalized numbers and the result is the largest representable normalized number
You add two large normalized numbers and the result overflows to Inifinity
You add a large normalized number and a small normalized number and the result is the largest representable normalized number
You add a large normalized numbers and a small normalized number and the result overflows to Infinity
10/2/08 - Directed Random Test
Copyright Joanne DeGroat, ECE, OSU

9. Test for the other boundary
Test for the normalized/denormalized boundary
Add/Subtract two normalized numbers with the result being
The smallest normalized number
The largest denormalized number
Add/Subtract a normalized number and a denormalized number with the result beign
10/2/08 - Directed Random Test
Copyright Joanne DeGroat, ECE, OSU

10. More test for the boundary
Add/Subtract two denormalized numbers with the result beign
The smallest normalized number
The largest denormalized number
One you are confident you have the boundary conditions covered you can now use random test generation
10/2/08 - Directed Random Test
Copyright Joanne DeGroat, ECE, OSU

11. The bulk of the operational space
These special cases are less than 1% of the total test space.
Need to apply vectors such that your confidence is high that all parts of the unit have been sufficiently exercised.
Can design test vectors to specifically test having a result with a leading 1 bit in each position.
Can have test vectors that result in no carry ripple and those that have maximum carry ripple
10/2/08 - Directed Random Test
Copyright Joanne DeGroat, ECE, OSU

12. Copyright 2008 - Joanne DeGroat, ECE, OSU
The use of random
Can use constrained random to generate a lot of test.
For normalized number operation - Start by breaking up vector into fields.
The sign, the exponent and the fractional part
Generate the exponents randomly between 1 and 254
Generate the fractional part randomly – knowing you have the assumed 1.
For Denormalized
Here only need the fractional part
10/2/08 - Directed Random Test
Copyright Joanne DeGroat, ECE, OSU

13. Constraining the random
Want to subtract a normalized and denormalized to get either a normalized or denorm result.
Set the exponent and sign
Generate the fractional part randomly but constrain the range of the random value generated such that the result will be in a range to realized the test objective.
10/2/08 - Directed Random Test
Copyright Joanne DeGroat, ECE, OSU

14. Generation of Random Vectors
Numerous ways to generate the random vectors
C or C++ program
MATLAB script or program
By hand (but only for very limited cases)
A combination of these and others
10/2/08 - Directed Random Test
Copyright Joanne DeGroat, ECE, OSU