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אבשלום אלידע 0-320690 23 לאוניד פרואנצ'נקו 2 1052137- 3 CAD of VLSI Systems (046880) 21/01/03

Paper Review: Hole Analysis For Functional Coverage Data by Oded Lachish, Eitan Marcus, Shmuel Ur, Avi Ziv @IL.IBM. אבשלום אלידע 0-320690 23 לאוניד פרואנצ'נקו 2 1052137- 3 CAD of VLSI Systems (046880) 21/01/03. Functional Coverage. Functional Coverage -- A means of:

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אבשלום אלידע 0-320690 23 לאוניד פרואנצ'נקו 2 1052137- 3 CAD of VLSI Systems (046880) 21/01/03

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  1. Paper Review:Hole Analysis For Functional Coverage Databy Oded Lachish, Eitan Marcus, Shmuel Ur, Avi Ziv @IL.IBM אבשלום אלידע 0-32069023 לאוניד פרואנצ'נקו 21052137-3 CAD of VLSI Systems (046880) 21/01/03

  2. Functional Coverage • Functional Coverage -- A means of: • Measuring the efficiency of Functional Verification. • Finding how and in what directions to improve Test Generation in order to increase coverage. • And as a result, reach more corner verification cases and CATCH MORE BUGS !!! • Compare to older, less effective coverage methods (toggle, line, cross-state), Functional Coverage models closely the design functionality.

  3. Functional Coverage: Motivation • Just testing is not enough: • Manual testing (MT) time-consuming and only gives us relatively simple cases. • Efficient bug-finding with random testing (RT), but RT machine-resource consuming and needs to be tracked closely for efficiency with a dedicated tool … • The 1M$ question of verification: what level of coverage are we achieving?! Without dedicated tool, cannot answer this.

  4. Functional Coverage in a Nutshell • Define list (space) of complete functionality of design. Comprises of verification tasks i.e, cases we expect to reach. • Track testing results (mostly RT, also MT) and check which tasks were reached. (Groups of) tasks not reached are referred to as “holes”. • In order to “plug” the holes: • Change/improve test-generator or testing-environment as needed or, • Define restriction on coverage model if hole is not real case.

  5. Functional Coverage – Cntd. • An Iterative Process:Resume testing to check improvement in total tasks covered report coverage again • Cases-reached / Total-Case-Space = % Coverage

  6. Functional Coverage: An Iterative Process

  7. Example Coverage Model:A Network Switch Receive Port • Define attribute groups. Rx-port consists of <Packet received, Ports action Decision> pairs. • Define attributes, for each attr. its possible values:

  8. Receive Port – Packet Received

  9. Receive Port – Decision

  10. Hole Analysis • Concise presentation of coverage data crucial for effective analysis of coverage results. • Mere list of tasks not reached – all but meaningless! • Group together multiple single-element holes,Projected Holes: n-dimensional holes.  More significance and clarity than mere list of uncovered tasks. • Case space: <type,Length,cast,CRCin, Fwd,Reject,CRCout> has N=7 dimensions. • 0-dimensional hole: one point in case-space not reached:<IP,64-127,MC,intact,own dev port5,reject,CRC> didn’t happen. • n-dimensional hole: no event reached for any of the cases whereN-n+1 attributes were at a fixed value:<IPoEth,*,*,*,reject,*,*>  hole of n=5, no IP pkts were rejected for any reason! • Group together 0-dim. holes to more significant n-dim. holes.

  11. Hole Analysis: Coverage Data Presentation • Aggregated Holes • Group holes together based on Hamming Distance = 1. (Hamming dist. = # of different attributes). Example with 2 attributes (1-covered, 0-uncovered)  better: Partitioned Holes.

  12. Conclusions • Coverage emerging as critical tool in verif. flow: • Close tracking of testing environment effectiveness, closely linked to RT. • Assessment (in %) of degree of above effectiveness, gives a feel of how much more verif. needs to be done. • Considering ever-increasing size&complexity of today’s industry designs, keeping verif. up to the task without diverse&informative coverage tool – next to impossible. • Diverse&informative: in-depth Hole-Analysis, smart grouping of holes to “serve” for the verif. engineer.

  13. Food for Thought • Modeling of functional coverage closely coupled to many subjects studied in the course: • Data structures use BDD for compact representation of sets attributes. • Checking whether a task was covered  satisfiability. • Coverage and Formal-Verification: Two Sisters • Formal: state a rule  check for it’s tautology. • Coverage: state a rule in from of “task didn’t happen”  check that it is unsatisfied. • *) No mumbo-jumbo clip-art or meaningless graphics were used in the making of this paper review. Technion, Israel, January 2003. A.E, L.F.

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