Booleguru, the Propositional Polyglot (Short Paper)

Abstract 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.