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SyGuS-Comp 2017: Results and Analysis

Author(s)
Alur, Rajeev; Fisman, Dana; Singh, Rishabh; Solar-Lezama, Armando
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Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/
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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.
Date issued
2017
URI
https://hdl.handle.net/1721.1/134711
Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Journal
Electronic Proceedings in Theoretical Computer Science
Publisher
Open Publishing Association

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