Results and Analysis of SyGuS-Comp'15
Abstract
Syntax-Guided Synthesis (SyGuS) is the computational problem of finding an implementation f that meets both a semantic constraint given by a logical formula in a background theory T, and a syntactic constraint given by a grammar G, which specifies the allowed set of candidate implementations. Such a synthesis problem can be formally defined in SyGuS-IF, a language that is built on top of SMT-LIB. The Syntax-Guided Synthesis Competition (SyGuS-comp) is an effort to facilitate, bring together and accelerate research and development of efficient solvers for SyGuS by providing a platform for evaluating different synthesis techniques on a comprehensive set of benchmarks. In this year's competition we added two specialized tracks: a track for conditional linear arithmetic, where the grammar need not be specified and is implicitly assumed to be that of the LIA logic of SMT-LIB, and a track for invariant synthesis problems, with special constructs conforming to the structure of an invariant synthesis problem. This paper presents and analyzes the results of SyGuS-comp'15.
Keywords
Cite
@article{arxiv.1602.01170,
title = {Results and Analysis of SyGuS-Comp'15},
author = {Rajeev Alur and Dana Fisman and Rishabh Singh and Armando Solar-Lezama},
journal= {arXiv preprint arXiv:1602.01170},
year = {2016}
}
Comments
In Proceedings SYNT 2015, arXiv:1602.00786