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Quantifier Elimination With Structural Learning

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abstract

We consider the Quantifier Elimination (QE) problem for propositional CNF formulas with existential quantifiers. QE plays a key role in formal verification. Earlier, we presented an approach based on the following observation. To perform QE, one just needs to add a set of clauses depending on free variables that makes the quantified clauses (i.e. clauses with quantified variables) redundant. To implement this approach, we introduced a branching algorithm making quantified clauses redundant in subspaces and merging the results of branches. To implement this algorithm we developed the machinery of D-sequents. A D-sequent is a record stating that a quantified clause is redundant in a specified subspace. Redundancy of a clause is a structural property (i.e. it holds only for a subset of logically equivalent formulas as opposed to a semantic property). So, re-using D-sequents is not as easy as re-using conflict clauses in SAT-solving. In this paper, we address this problem. We introduce a new definition of D-sequents that enables their re-usability. We develop a theory showing under what conditions a D-sequent can be safely re-used.

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cs.LO 1

years

2019 1

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UNVERDICTED 1

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Partial Quantifier Elimination With Learning

cs.LO · 2019-06-25 · unverdicted · novelty 6.0

A new PQE algorithm learns D-sequents for reuse and backtracks upon proving a single clause redundant, outperforming its predecessor experimentally.

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  • Partial Quantifier Elimination With Learning cs.LO · 2019-06-25 · unverdicted · none · ref 21 · internal anchor

    A new PQE algorithm learns D-sequents for reuse and backtracks upon proving a single clause redundant, outperforming its predecessor experimentally.