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arXiv · 1904.07146

SyGuS-Comp 2018: Results and Analysis

Rajeev Alur·Dana Fisman·Saswat Padhi·Rishabh Singh·Abhishek Udupa
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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 $\phi$ in a background theory $\mathbb{T}$, 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 the SyGuS input format (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 the 5th SyGuS-Comp, five solvers competed on over 1600 benchmarks across various tracks. This paper presents and analyses the results of this year's (2018) SyGuS competition.

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Rajeev Alur, Dana Fisman, Saswat Padhi, Rishabh Singh, Abhishek Udupa. 2019-04-12. SyGuS-Comp 2018: Results and Analysis. https://arxiv.org/abs/1904.07146

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