A Survey of Satisfiability Modulo Theory

Satisfiability modulo theory (SMT) consists in testing the satisfiability of first-order formulas over linear integer or real arithmetic, or other theories. In this survey, we explain the combination of propositional satisfiability and decision procedures for conjunctions known as DPLL(T), and the alternative "natural domain" approaches. We also cover quantifiers, Craig interpolants, polynomial arithmetic, and how SMT solvers are used in automated software analysis.Comment: Computer Algebra in Scientific Computing, Sep 2016, Bucharest, Romania. 201

Proof Generation in CDSAT

The main ideas in the CDSAT (Conflict-Driven Satisfiability) framework for SMT are summarized, leading to approaches to proof generation in CDSAT.Comment: In Proceedings PxTP 2021, arXiv:2107.0154

A Survey of Satisfiability Modulo Theory

International audienceSatisfiability modulo theory (SMT) consists in testing the satisfiability of first-order formulas over linear integer or real arithmetic, or other theories. In this survey, we explain the combination of propositional satisfiability and decision procedures for conjunctions known as DPLL(T), and the alternative "natural domain" approaches. We also cover quantifiers, Craig interpolants, polynomial arithmetic, and how SMT solvers are used in automated software analysis

Theory Combination: Beyond Equality Sharing

International audienceSatisfiability is the problem of deciding whether a formula has a model. Although it is not even semidecidable in first-order logic, it is decidable in some first-order theories or fragments thereof (e.g., the quantifier-free fragment). Satisfiability modulo a theory is the problem of determining whether a quantifier-free formula admits a model that is a model of a given theory. If the formula mixes theories, the considered theory is their union, and combination of theories is the problem of combining decision procedures for the individual theories to get one for their union. A standard solution is the equality-sharing method by Nelson and Oppen, which requires the theories to be disjoint and stably infinite. This paper surveys selected approaches to the problem of reasoning in the union of disjoint theories, that aim at going beyond equality sharing, including: asymmetric extensions of equality sharing, where some theories are unrestricted, while others must satisfy stronger requirements than stable infiniteness; superposition-based decision procedures; and current work on conflict-driven satisfiability (CDSAT)

Conflict-driven satisfiability for theory combination: lemmas, modules, and proofs

Search-based satisfiability procedures try to build a model of the input formula by simultaneously proposing candidate models and deriving new formulae implied by the input. Conflict-driven procedures perform nontrivial inferences only when resolving conflicts between formulae and assignments representing the candidate model. CDSAT (Conflict-Driven SATisfiability) is a method for conflict-driven reasoning in unions of theories. It combines solvers for individual theories as theory modules within a solver for the union of the theories. In this article, we add lemma learning to CDSAT; we show that theory modules for several theories of practical interest fulfill the requirements for completeness and termination of CDSAT; and we present two ways to enrich CDSAT with proof generation. First, we present a proof-carrying CDSAT transition system that produces proof objects in memory accommodating multiple proof formats. Alternatively, we apply to CDSAT the LCF approach to proofs from interactive theorem proving, by defining a kernel of reasoning primitives that guarantees that CDSAT proofs are correct by construction

Unbounded Superoptimization

Our aim is to enable software to take full advantage of the capabilities of emerging microprocessor designs without modifying the compiler. Towards this end, we propose a new approach to code generation and optimization. Our approach uses an SMT solver in a novel way to generate efficient code for modern architectures and guarantee that the generated code correctly implements the source code. The distinguishing characteristic of our approach is that the size of the constraints does not depend on the candidate sequence of instructions. To study the feasibility of our approach, we implemented a preliminary prototype, which takes as input LLVM IR code and uses Z3 SMT solver to generate ARMv7-A assembly. The prototype handles arbitrary loop-free code (not only basic blocks) as input and output. We applied it to small but tricky examples used as standard benchmarks for other superoptimization and synthesis tools. We are encouraged to see that Z3 successfully solved complex constraints that arise from our approach. This work paves the way to employing recent advances in SMT solvers and has a potential to advance SMT solvers further by providing a new category of challenging benchmarks that come from an industrial application domain

Building Better Bit-Blasting for Floating-Point Problems

An effective approach to handling the theory of floating-point is to reduce it to the theory of bit-vectors. Implementing the required encodings is complex, error prone and requires a deep understanding of floating-point hardware. This paper presents SymFPU, a library of encodings that can be included in solvers. It also includes a verification argument for its correctness, and experimental results showing that its use in CVC4 out-performs all previous tools. As well as a significantly improved performance and correctness, it is hoped this will give a simple route to add support for the theory of floating-point

Satisfiability Modulo Finite Fields

We study satisfiability modulo the theory of finite fields and give a decision procedure for this theory. We implement our procedure for prime fields inside the cvc5 SMT solver. Using this theory, we con- struct SMT queries that encode translation validation for various zero knowledge proof compilers applied to Boolean computations. We evalu- ate our procedure on these benchmarks. Our experiments show that our implementation is superior to previous approaches (which encode field arithmetic using integers or bit-vectors)

Nelson Oppen combination as a rewrite theory

Solving Satisfiability Modulo Theories (SMT) problems in a key piece in automating tedious mathematical proofs. It involves deciding satisfiability of formulas of a decidable theory, which can often be reduced to solving systems of equalities and disequalities, in a variety of theories such as linear and non-linear real and integer arithmetic, arrays, uninterpreted and Boolean algebra. While solvers exist for many such theories or their subsets, it is common for interesting SMT problems to span multiple theories. SMT solvers typically use refinements of the Nelson-Oppen combination method, an algorithm for producing a solver for the quantifier free fragment of the combination of a number of such theories via cooperation between solvers of those theories, for this case. Here, we present the Nelson-Oppen algorithm adapted for an order-sorted setting as a rewriting logic theory. We implement this algorithm in the Maude System and instantiate it with the theories of real and integer matrices to demonstrate its use in automated theorem proving, and with hereditarily finite sets with reals to show its use with non-convex theories. This is done using both SMT solvers written in Maude itself via reflection (Variant-based satisfiability) and using external solvers (CVC4 and Yices). This work can be considered a first step towards building a rich ecosystem of cooperating SMT solvers in Maude, that modeling and automated theorem proving tools typically written using the Maude System can leverage