REVIEW 2 cited by
The SyGuS Language Standard Version 2.1
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
read the original abstract
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.
Forward citations
Cited by 2 Pith papers
-
Recursive Program Synthesis from Sketches and Mixed-Quantifier Properties
Cataclyst synthesizes recursive programs from mixed-quantifier first-order specs by synthesizing Skolem witness functions alongside the target program and pruning candidates with counterexample-derived syntactic constraints.
-
Online Prompt Selection for Program Synthesis
An online multi-armed bandit that selects among symbolic solvers and LLM-prompt combinations for program synthesis solves 37.2% more queries than the best single solver and reaches 96% of the virtual best solver's per...
Discussion (0). Continue with ORCID to comment.