SyGuS-Comp 2017: Results and Analysis
Name
1711.11438v1.pdf
Description
Published version
Size
1.33 MB
Format
Adobe PDF
Checksum (MD5)
3ed829245e6c1fba7a87e55174fc33d8
Author(s)
Alur, Rajeev
Fisman, Dana
Singh, Rishabh
Solar-Lezama, Armando
Date Issued
2017
Journal
Electronic Proceedings in Theoretical Computer Science
Publisher
Open Publishing Association
Version
Final published version
Abstract
© 2017 Open Publishing Association. All rights reserved. Syntax-Guided Synthesis (SyGuS) is the computational problem of finding an implementation f that meets both a semantic constraint given by a logical formula j 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 six new solvers competed on over 1500 benchmarks. This paper presents and analyses the results of SyGuS-Comp'17.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.4204/EPTCS.260.9
