Download Advanced Formal Verification by Rolf Drechsler PDF

By Rolf Drechsler

Advanced Formal Verification exhibits the newest advancements within the verification area from the views of the consumer and the developer. global top specialists describe the underlying tools of cutting-edge verification instruments and describe a variety of eventualities from business perform. within the first a part of the booklet the center suggestions of modern day formal verification instruments, resembling SAT and BDDs are addressed. moreover, multipliers, that are recognized to be tricky, are studied. the second one half provides perception in expert instruments and the underlying technique, similar to estate checking and statement dependent verification. eventually, analog elements must be thought of to deal with whole approach on chip designs.

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16 Let F be a set of clauses. Denote by supp(F) the set of variables whose literals occur in clauses of F . 14 ADVANCED FORMAL VERIFICATION To estimate the complexity of obtaining the function existentially implied by F in general resolution, we need the following proposition. 4 Let F be a set of clauses that implies a clause K. Then there is a sequence of at most 3|supp(F )| resolution steps that results in the derivation of the clause K or a clause that implies K. Proof. Denote by F the formula that is obtained from F by making the assignments that set the literals of K to 0 (and removing the satisfied clauses and the literals set to 0).

Indeed, let us make the following two very plausible assumptions. 7 (we will refer to them as specification driven proofs) are “much shorter” than any other kind of resolution proofs. Second assumption is that finding a non-trivial CS of two Boolean circuits N1 and N2 is hard. If the two assumptions above are true then formulas from M ∗ should be hard. Indeed, specification driven resolution proofs very closely follow a CS of N1 and N2 . So knowing a short resolution proof of the unsatisfiability of F ,F ∈ M ∗ one could easily recover the CS that “guided” that proof.

Since A and B are primary input variables they are encoded with a minimum length code and q 1 (A)=q 2 (A) and q 1 (B)=q 2 (B) where q 1 (a0 )=0, q 1 (a1 )=1, q 1 (b0 )=00, q 1 (b1 )=01, q 1 (b2 )=10, q 1 (b3 )=11. Finally, the encodings q 1 (C) and q 2 (C) are q 1 (c0 )=00, q 1 (c1 )=10, q1 (c2 ) = 01 and q 2 (c0 )=100, q 2 (c1 )= 010, q 2 (c2 )=001. 3 may not include all the variables of v(A) and/or v(B) is that the function G(A, B) may not distinguish some values of A or B. ) So to implement G(A, B) the circuit I may need only a subset of variables of v(A) ∪ v(B).

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