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Number of different prefixes generated from of the 2008 non-CNF benchmark set with all strategy combinations. Each strategy has 492 formulas.
Source publication
Modern solvers for quantified Boolean formulas (QBFs) process formulas in prenex form, which divides each QBF into two parts: the quantifier prefix and the propositional matrix. While this representation does not cover the full language of QBF, every non-prenex formula can be transformed to an equivalent formula in prenex form. This transformation...
Context in source publication
Context 1
... we focus on the formulas of the QBFEval'08 benchmark set in the following. Table 1 shows the results for the QCIR solvers and Table 2 shows the number of different prefixes that were generated with all strategy combinations. For QuAbS, QFUN, and CQESTO we see a clear difference between the best and worst shifting strategy. ...Similar publications
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Citations
... Finally, we explained how Booleguru is used to generate new encodings, using the embedded Lua, Fennel, and Python scripting support. Booleguru already proved itself as a valuable tool during the QBFGallery 2023, for revisiting quantifier shifting in QBF [10], and other projects. ...
Recent approaches on verification and reasoning solve SAT and QBF encodings using state-of-the-art SMT solvers, as it “makes implementation much easier”. The ease-of-use of these solvers make SAT and QBF solvers less visible to users of solvers—who are maybe from different research communities—potentially not exploiting the power of state-of-the-art tools. In this work, we motivate the need to build bridges over the widening solver-gap and introduce Booleguru , a tool to convert between formats for logic formulas. It makes SAT and QBF solvers more accessible by using techniques known from SMT solvers, such as advanced Python interfaces like Z3Py and easily generatable languages like SMT-LIB, integrating them to our conversion tool. We then introduce a language to manipulate and combine multiple formulas, optionally applying transformations for quickly prototyping encodings. Booleguru ’s advanced scripting capabilities form a programming environment specialized for Boolean logic, offering a more efficient way to develop novel problem encodings.
