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Semantics-Guided Synthesis (SemGuS) is a programmable framework for defining synthesis problems in a domain- and solver-agnostic way. This paper presents the standardized SemGuS format, together with an open-source toolkit that provides a parser, a verifier, and enumerative SemGuS solvers. The paper also describes an initial set of SemGuS benchmarks, which form the basis for comparing SemGuS solvers, and presents an evaluation of the baseline enumerative solvers.

We present a number of first- and second-order extensions to SMT theories specifically aimed at representing and analyzing SQL queries with join, projection, and selection operations. We support reasoning about SQL queries with either bag or set semantics for database tables. We provide the former via an extension of a theory of finite bags and the latter via an extension of the theory of finite relations. Furthermore, we add the ability to reason about tables with null values by introducing a theory of nullable sorts based on an extension of the theory of algebraic datatypes. We implemented solvers for these theories in the SMT solver cvc5 and evaluated them on a set of benchmarks derived from public sets of SQL equivalence problems.

The classical formulation of the program-synthesis problem is to find a program that meets a correctness specification given as a logical formula. Syntax-guided synthesis (SyGuS) is a standardized format for specifying the correctness specification with a syntactic template that constrains the space of allowed implementations. The input to SyGuS consists of a background theory, a semantic correctness specification for the desired program given by a logical formula, and a syntactic set of candidate implementations given by a grammar. The computational problem then is to find an implementation from the set of candidate expressions that satisfies the specification in the given theory. The formulation of the problem builds on SMT-LIB. This document defines the SyGuS 2.1 standard, which is intended to be used as the standard input and output language for solvers targeting the syntax-guided synthesis problem. It borrows many concepts and language constructs from the standard format for Satisfiability Modulo Theories (SMT) solvers, the SMT-LIB 2.6 standard., Comment: 36 pages, introduced in the SYNT workshop at CAV 2021

For many users of Satisfiability Modulo Theories (SMT) solvers, the solver's performance is the main bottleneck in their application. One promising approach for improving performance is to leverage the increasing availability of parallel and cloud computing. However, despite many efforts, the best parallel approach to date consists of running a portfolio of solvers, meaning that performance is still limited by the best possible sequential performance. In this paper, we revisit divide-and-conquer approaches to parallel SMT, in which a challenging problem is partitioned into several subproblems. We introduce several new partitioning strategies and evaluate their performance, both alone as well as within portfolios, on a large set of difficult SMT benchmarks. We show that hybrid portfolios that include our new strategies can significantly outperform traditional portfolios for parallel SMT., Comment: Submitted to FMCAD 2023