Z3: Applications, Enablers, Challenges and Directions

Modern program analysis and model-based tools are increasingly complex and multi-faceted software systems. However, at their core is invariably a component using a logic for describing states and transformations between system states. Logic inferences engines are then critical for the functionality of these systems. A commonly adapted approach has been to use a custom solver, built and tailored for the specific application. Custom solvers come with custom limitations: extending and scaling these often require a high investment. Taking as a starting point the solver Z3, developed at Microsoft Research; we describe how an efficient, scalable and expressive solver for Satisfiability Modulo Theories (SMT) is part of changing this landscape. Tools can now use the SMT solver with advantage to solve logic-related problems at a relatively highlevel of abstraction while attaining scalability and features that custom solvers would have to duplicate. We summarize 10 current applications of the Z3 solver and relate these to 10 main technological enabling factors. With every application there is a new opportunity, and with every solution there is a new challenge problem. Thus, we also summarize 10 challenges and 10 aspiring directions in the context of Z3 in particular, and for SMT solvers in general.