Partial Quantifier Elimination By Certificate Clauses

We study partial quantifier elimination (PQE) for propositional CNF formulas. In contrast to full quantifier elimination, in PQE, one can limit the set of clauses taken out of the scope of quantifiers to a small subset of target clauses. The appeal of PQE is twofold. First, PQE can be dramatically simpler than full quantifier elimination. Second, it provides a language for performing incremental computations. Many verification problems (e.g. equivalence checking and model checking) are inherently incremental and so can be solved in terms of PQE. Our approach is based on deriving clauses depending only on unquantified variables that make the target clauses $\mathit{redundant}$. Proving redundancy of a target clause is done by construction of a ``certificate'' clause implying the former. We describe a PQE algorithm called $\mathit{START}$ that employs the approach above. We apply $\mathit{START}$ to generating properties of a design implementation that are not implied by specification. The existence of an $\mathit{unwanted}$ property means that this implementation is buggy. Our experiments with HWMCC-13 benchmarks suggest that $\mathit{START}$ can be used for generating properties of real-life designs

Partial Quantifier Elimination

We consider the problem of Partial Quantifier Elimination (PQE). Given formula exists(X)[F(X,Y) & G(X,Y)], where F, G are in conjunctive normal form, the PQE problem is to find a formula F*(Y) such that F* & exists(X)[G] is logically equivalent to exists(X)[F & G]. We solve the PQE problem by generating and adding to F clauses over the free variables that make the clauses of F with quantified variables redundant. The traditional Quantifier Elimination problem (QE) is a special case of PQE where G is empty so all clauses of the input formula with quantified variables need to be made redundant. The importance of PQE is twofold. First, many problems are more naturally formulated in terms of PQE rather than QE. Second, in many cases PQE can be solved more efficiently than QE. We describe a PQE algorithm based on the machinery of dependency sequents and give experimental results showing the promise of PQE

Verification of Sequential Circuits by Tests-As-Proofs Paradigm

We introduce an algorithm for detection of bugs in sequential circuits. This algorithm is incomplete i.e. its failure to find a bug breaking a property P does not imply that P holds. The appeal of incomplete algorithms is that they scale better than their complete counterparts. However, to make an incomplete algorithm effective one needs to guarantee that the probability of finding a bug is reasonably high. We try to achieve such effectiveness by employing the Test-As-Proofs (TAP) paradigm. In our TAP based approach, a counterexample is built as a sequence of states extracted from proofs that some local variations of property P hold. This increases the probability that a) a representative set of states is examined and that b) the considered states are relevant to property P. We describe an algorithm of test generation based on the TAP paradigm and give preliminary experimental results