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Automatic Abstraction Refinement for GSTE Yan Chen, Yujing He, and Fei Xie Portland State University Jin Yang Intel Nov 13, 2007
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Our Contributions AutoGSTE – An automatic approach to abstraction refinement for GSTE Quickly converge to good abstractions that enable verifications that are not possible before Allow assertion graphs to be high-level w/o adapting too much to circuit implementation 2
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Outline Overview of (G)STE Quaternary Abstraction and its Imprecision Our Solution – AutoGSTE Counterexample-guided abstraction refinement Model refinement and specification refinement Experiments Conclusion & Future Work 3
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Symbolic Trajectory Evaluation [Bryant & Seger] Scalability Model checking complexity largely depends on the complexity of the assertion rather than the circuit Pros: Highly efficient Cons: False negatives due to insufficient input constraints R. Tzoref, O. Grumberg, Automatic refinement and vacuity detection for STE, CAV’06 J. Roorda, K. Clarssen, Sat-based assistance to abstraction refinement for STE, CAV’06 Only properties over finite time GSTE 4
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Generalized STE [Yang & Seger] ω -regular properties represented by assertion graphs G = { (V, v 0, E, ant, cons) } Non-deterministic execution Fixed-point computation 5
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GSTE Algorithm 6 Algorithm: GSTE(G, post) (* initialize symbolic simulation *) 1. for each edge e in G 2. if e is from the initial vertex 3. sim(e) := ant(e); 4. put e in EventQueue; 5. else 6. sim(e) := { }; (* perform symbolic simulation *) 7. while EventQueue is not empty 8. get an edge e from the queue, 9. for each successor edge e’ of e begin 10. sim(e’) := sim(e’) post(sim(e)) ant(e’); 11. if there is a change in sim(e’) 12. put e’ into EventQueue; end (* check consequence *) 13. for each edge e in G 14. if !(sim(e) cons(e)) return false; 15. return true; end.
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Outline Overview of (G)STE Quaternary Abstraction and its Imprecision Our Solution – AutoGSTE Counterexample-guided abstraction refinement Model refinement and specification refinement Experiments Conclusion & Future Work 7
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Quaternary-Value Logic (Unknown) (Conflict) Information Partial OrderPropagation of “Unknown” Two sides of a coin Significantly reduce state spaces by quaternary abstraction Over abstractions cause false negatives 8
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1 X Causes of False Negative: Quaternary State Set Unions 1 1 1 A B Out 1 0 1X X X Abs. 9 0 1 sim(e’) := sim(e’) post(sim(e)) ant(e’); 11 Check whether the output is always 1 under certain inputs
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Causes of False Negative: Existentially Quantified-Out Symbolic Variables c1,c2 is existentially quantified out after every single step simulation 10 [A=c1, B=(!c1|c2)] Out=A|B=c1|(!c1|c2)=1 [A=X, B=X] Out=A|B=X A B Out 1 1 1 0 0 1
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Outline Overview of (G)STE Quaternary Abstraction and its Imprecision Our Solution – AutoGSTE Counterexample-guided abstraction refinement Model refinement and specification refinement Experiments Conclusion & Future Work 11
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AutoGSTE: Automatic Abstraction Refinement (1) GSTE Circuit Impl. Assertion Graph Assertion holds Counter Example (2) Counter Example Analysis Assertion fails Causes of Imprecision (3) Abstraction Refinement Refined Abstraction Abstraction refinement: (monotonic) (1) Constraining inputs with symbolic constants/variables (2) Model refinement: introducing precise nodes (3) Spec refinement: assertion graph transformations Causes of imprecision in GSTE’s quaternary abstraction: (1) Under-constrained inputs; (2) Quaternary state set unions; (3) Existentially quantified-out symbolic variables
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Counter Example Analysis Counter Example [(edge 1,src 1,dest 1 ),…,(edge T, src T,dest T )] Identify “X” nodes in dest T that violates consequent on edge T Backtrack to identify the causes for “X” node N In the end, the following causes will be identified: Output circuit nodes/assertion edges on which Xs are introduced. 13 InputUnionWeak
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AutoGSTE: Automatic Abstraction Refinement (1) GSTE Circuit Impl. Assertion Graph Assertion holds Counter Example (2) Counter Example Analysis Assertion fails Causes of Imprecision (3) Abstraction Refinement Refined Abstraction Abstraction refinement: (1) Constraining inputs with symbolic constants/variables (2) Model refinement: introducing precise nodes (3) Spec refinement: assertion graph transformations Causes of imprecision in GSTE’s quaternary abstraction: (1) Under-constrained inputs; (2) Quaternary state set unions; (3) Existentially quantified-out symbolic variables
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Model Refinement Symbolic Indexing (Verifier has to encode it in the specification) Abs. Partition Abs.rew. Finer Partition 15
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Model Refinement (Cont.) Precise Nodes: Circuit nodes that must always have boolean values by symbolic indexing [Yang and Seger, FMCAD’02] Manually specify precise nodes to eliminate Xs caused by both unions and weaks. AutoGSTE automatically marks precise nodes Mark all the identified nodes as precise Mark one node at a time (control signals first?) 16
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Specification Refinement Loop unrolling transformations address unions Allow the specification to be high level Dynamically adapt to the real computation flow of the circuit …… 17
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Automating loop unrolling Unroll each problematic edge to prevent unwanted state set unions Specification Refinement (Cont.) 18 1 2 3 4
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Case splitting transformations address weaks Symbolic variables symbolically index a set of edges with scalar values Remember the variable values by case splitting Specification Refinement (Cont.) 19
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Outline Overview of (G)STE Quaternary Abstraction and its Imprecision Our solution – AutoGSTE Counterexample-guided abstraction refinement Model Refinement.vs. Specification Refinement Experiments Conclusion & Future Work 20
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Experiment: FIFO 21
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FIFO Model Refinement CircuitMark precise nodes all at onceMark precise nodes one a time FIFO Depth # of Nodes # of Iter. # of P. Nodes Time (Sec.) BDD Nodes # of P. Nodes Time (Sec.) BDD Nodes 3181150.12 10232 30.26 8996 8296170.4 32923 40.81 26708 16476191.1 72189 52.37 58250 247871112.38 131236 66.83 104246 Better than manual analysis! 22
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FIFO Specification Refinement CircuitGSTE on Original assertion graphSemantic-Preserving Transformation FIFO Depth # of Edges Time (Sec.) BDD Nodes Mem (MB) Result # of Edges Time (Sec.) BDD Nodes Mem (MB) Result 3110.01517Fail310.23617Pass 8260.02517Fail2012.69619Pass 16500.04517Fail78517.3626Pass 24740.07517Fail175354.2639Pass Too complex to do manually! 23
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Conclusion & Future Work An automatic approach to abstraction refinement for GSTE Quickly converge to good abstractions Future work Identify minimal set of precise nodes Reduce unnecessary loop-unrolling/case-splitting Integrate model refinement and spec refinement 27
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