DepQBF 6.0: A Search-Based QBF Solver Beyond Traditional QCDCL

We present the latest major release version 6.0 of the quantified Boolean formula (QBF) solver DepQBF, which is based on QCDCL. QCDCL is an extension of the conflict-driven clause learning (CDCL) paradigm implemented in state of the art propositional satisfiability (SAT) solvers. The Q-resolution calculus (QRES) is a QBF proof system which underlies QCDCL. QCDCL solvers can produce QRES proofs of QBFs in prenex conjunctive normal form (PCNF) as a byproduct of the solving process. In contrast to traditional QCDCL based on QRES, DepQBF 6.0 implements a variant of QCDCL which is based on a generalization of QRES. This generalization is due to a set of additional axioms and leaves the original Q-resolution rules unchanged. The generalization of QRES enables QCDCL to potentially produce exponentially shorter proofs than the traditional variant. We present an overview of the features implemented in DepQBF and report on experimental results which demonstrate the effectiveness of generalized QRES in QCDCL.Comment: 12 pages + appendix; to appear in the proceedings of CADE-26, LNCS, Springer, 201

Synthesizing Multiple Boolean Functions using Interpolation on a Single Proof

It is often difficult to correctly implement a Boolean controller for a complex system, especially when concurrency is involved. Yet, it may be easy to formally specify a controller. For instance, for a pipelined processor it suffices to state that the visible behavior of the pipelined system should be identical to a non-pipelined reference system (Burch-Dill paradigm). We present a novel procedure to efficiently synthesize multiple Boolean control signals from a specification given as a quantified first-order formula (with a specific quantifier structure). Our approach uses uninterpreted functions to abstract details of the design. We construct an unsatisfiable SMT formula from the given specification. Then, from just one proof of unsatisfiability, we use a variant of Craig interpolation to compute multiple coordinated interpolants that implement the Boolean control signals. Our method avoids iterative learning and back-substitution of the control functions. We applied our approach to synthesize a controller for a simple two-stage pipelined processor, and present first experimental results.Comment: This paper originally appeared in FMCAD 2013, http://www.cs.utexas.edu/users/hunt/FMCAD/FMCAD13/index.shtml. This version includes an appendix that is missing in the conference versio

Incremental QBF Solving

We consider the problem of incrementally solving a sequence of quantified Boolean formulae (QBF). Incremental solving aims at using information learned from one formula in the process of solving the next formulae in the sequence. Based on a general overview of the problem and related challenges, we present an approach to incremental QBF solving which is application-independent and hence applicable to QBF encodings of arbitrary problems. We implemented this approach in our incremental search-based QBF solver DepQBF and report on implementation details. Experimental results illustrate the potential benefits of incremental solving in QBF-based workflows.Comment: revision (camera-ready, to appear in the proceedings of CP 2014, LNCS, Springer

Dependency Schemes in QBF Calculi: Semantics and Soundness

We study the parametrisation of QBF resolution calculi by dependency schemes. One of the main problems in this area is to understand for which dependency schemes the resulting calculi are sound. Towards this end we propose a semantic framework for variable independence based on ‘exhibition’ by QBF models, and use it to express a property of dependency schemes called full exhibition that is known to be sufficient for soundness in Q-resolution. Introducing a generalised form of the long-distance resolution rule, we propose a complete parametrisation of classical long-distance Q-resolution, and show that full exhibition remains sufficient for soundness. We demonstrate that our approach applies to the current research frontiers by proving that the reflexive resolution path dependency scheme is fully exhibited

Results on Extensions of the Satisfability Problem

The satisfiability problem (SAT) and its extensions have become indispensible tools in artificial intelligence, verification, and many other domains. Extensions of the problem such as model counting, quantified Boolean formulae (QBF), and MAX-SAT have similarly seen increased study and applications. This thesis provides a survey on SAT, and then presents novel results related to model counting and random QBF. Chapter 3 gives a general technique for computing inclusion-exclusion sums more efficiently for the purpose of model counting. The main contribution is a subsumption technique which reduces computational overhead. Treating an inclusion-exclusion sum's computation as tree exploration, subsumption allows us to prune large subtrees. We also give a better worst-case upper bound on the algorithm's running time, improving it from exponential in the number of clauses to the number of variables in a CNF formula. Chapter 5 describes a new phase transition in random QBF, along with related results on random QBF models. The clause-to-variable ratio phase transition identified in random $k$-SAT has been the subject of intense study on what makes a SAT instance intractable, and recent work has studied a similar transition in random QBF. Here we show that a satisfiability threshold exists around phase transitions arising from altering the fraction of existentially versus universally quantified variables in a formula. In chapter 6 we revisit work on generating trivially false formulas in several related random QBF models, giving precise bounds for how likely they are to occur