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IEEE TRANSACTIONS ON COMPUTERS, VOL. 56, NO. 4, APRIL 2007 P ROPERTIES I NCOMPLETENESS E VALUATION BY F UNCTIONAL V ERIFICATION 1
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M AIN CONTRIBUTION A coverage methodology based on a combination of static and dynamic verification that allows us to reduce the evaluation time with respect to pure formal approaches 2
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I NTRODUCTION Simulation-based techniques Lack of exhaustiveness Formal verification Overcome the exhaustiveness problem Properties are derived from informal design specifications. Model checking: prove the presence of bugs, but not their absence 3
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V ERIFICATION F LOW B ASED ON M ODEL C HECKING 4
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I NTRODUCTION – M ODEL C HECKING To increase the effectiveness of model checking Vacuity detection: look for properties that hold in a model and can be strengthened without causing them to fail Property coverage: address the question of whether enough properties have been defined How many properties should be defined to completely check the implementation? Coverage metric! 5
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Mutation-based ACTL, LTL, and CTL State coverage path coverage transition-based coverage Implementation-based State explosion problem Cannot precisely reflect the completeness of properties 6 I NTRODUCTION – P REVIOUS W ORK How about use mutation coverage jointly with dynamic verification to address the quality of the model checking process?
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B ACKGROUND Kripke structure K = {S, S 0, R, L} FSM M = {I, O, S, s 0, R} Product machine M P = M 1 X P M 2 Retroactive network 7 Ι ε
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M ETHODOLOGY O VERVIEW 8
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G ENERATION OF F AULTY I MPLEMENTATIONS The proposed methodology is independent of the adopted fault model Different fault models can provide different estimations of the property completeness Functional fault model Bit coverage has been proved to be related to design errors Bit coverage fault model assumptions Bit failure: stuck-at 0 or stuck-at 1 Condition failure: stuck-at true or stuck-at false Single fault: A faulty implementation is generated for each fault 9
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G ENERATION OF F AULTY I MPLEMENTATIONS ( CONT.) Detectable faults 10
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G ENERATION OF F AULTY I MPLEMENTATIONS ( CONT.) A non-optimized algorithm If fail then f is ε-detectable Time-consuming and very likely state explosion 11
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E STIMATION OF G OLDEN M ODEL I NCOMPLETENESS Ƥ-detectable and Ƥ-det Property coverage 12
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E STIMATION OF G OLDEN M ODEL I NCOMPLETENESS ( CONT.) C P = 1 formal properties are complete w.r.t. a particular fault model Non-optimized algorithm 13
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E STIMATION OF G OLDEN M ODEL I NCOMPLETENESS ( CONT.) Witnesses and counterexamples Tools can provide witnesses and counterexamples for CTL and LTL properties Input witness and input counterexample 14
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W ITNESS C OVERAGE Property coverage can be estimated by using input witnesses Under some conditions, C P = C w 15
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P ROOF OF C P = C W 16 Consider the safety and liveness properties separately
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P ROOF OF C P = C W ( CONT.) 17
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P ROOF OF C P = C W ( CONT.) 18
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I NCREMENTAL P ROPERTY C OVERAGE C OMPUTATION 19
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C OVERAGE A CCURACY C OMPARISON Combining static and dynamic verification makes this methodology can deal with real industrial circuits. The methodology presented in this paper covers faults rather than states. Can estimate coverage more accurate (compare with previous works) 20
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E XPERIMENTAL R ESULTS 21
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I NSPIRE TO IC/CAD C ONTEST Functional fault model Estimate coverage by fault instead of properties 22
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