Syntax-Guided Synthesis

Rajeev Alur; Rastislav Bodik; Eric Dallal; Dana Fisman; Pranav Garg; Garvit Juniwal; Hadas Kress-Gazit; P. Madhusudan; Milo M. K. Martin; Mukund Raghothaman; Shamwaditya Saha; Sanjit A. Seshia; Rishabh Singh; Armando Solar-Lezama; Emina Torlak; Abhishek Udupa

doi:10.3233/978-1-61499-495-4-1

Syntax-Guided Synthesis

Rajeev Alur, Rastislav Bodik, Eric Dallal, Dana Fisman, Pranav Garg, Garvit Juniwal, Hadas Kress-Gazit, P. Madhusudan, Milo M. K. Martin, Mukund Raghothaman, Shamwaditya Saha, Sanjit A. Seshia, Rishabh Singh, Armando Solar-Lezama, Emina Torlak, Abhishek Udupa

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

The classical formulation of the program-synthesis problem is to find a
program that meets a correctness specification given as a logical formula. Recent work on program synthesis and program optimization illustrates many potential benefits of allowing the user to supplement the logical specification with a syntactic template that constrains the space of allowed implementations. Our goal is to identify the core computational problem common to these proposals in a logical framework. The input to the syntax-guided synthesis problem (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 so that it satisfies the specification in the given theory. We describe alternative solution strategies that combine learning, counter example analysis and constraint solving. We report on prototype implementations, and present experimental results on the set of benchmarks collected as part of the
first SyGuS-Comp competition held in July 2014.

Original language	English
Title of host publication	Dependable Software Systems Engineering
Editors	Maximilian Irlbeck, Doron Peled
Publisher	IOS Press
Pages	1-25
ISBN (Electronic)	9781614994954
ISBN (Print)	9781614994947
DOIs	https://doi.org/10.3233/978-1-61499-495-4-1
State	Published - 2015

Publication series

Name	Nato Science for Peace and Security Series D-Information and Communication Security

Keywords

Program Synthesis
Constraint Solving
Counterexamples
Machine Learning

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10.3233/978-1-61499-495-4-1

Cite this

Alur, R., Bodik, R., Dallal, E., Fisman, D., Garg, P., Juniwal, G., Kress-Gazit, H., Madhusudan, P., Martin, M. M. K., Raghothaman, M., Saha, S., Seshia, S. A., Singh, R., Solar-Lezama, A., Torlak, E., & Udupa, A. (2015). Syntax-Guided Synthesis. In M. Irlbeck, & D. Peled (Eds.), Dependable Software Systems Engineering (pp. 1-25). (Nato Science for Peace and Security Series D-Information and Communication Security). IOS Press. https://doi.org/10.3233/978-1-61499-495-4-1

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abstract = "The classical formulation of the program-synthesis problem is to find aprogram that meets a correctness specification given as a logical formula. Recent work on program synthesis and program optimization illustrates many potential benefits of allowing the user to supplement the logical specification with a syntactic template that constrains the space of allowed implementations. Our goal is to identify the core computational problem common to these proposals in a logical framework. The input to the syntax-guided synthesis problem (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 so that it satisfies the specification in the given theory. We describe alternative solution strategies that combine learning, counter example analysis and constraint solving. We report on prototype implementations, and present experimental results on the set of benchmarks collected as part of thefirst SyGuS-Comp competition held in July 2014.",

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author = "Rajeev Alur and Rastislav Bodik and Eric Dallal and Dana Fisman and Pranav Garg and Garvit Juniwal and Hadas Kress-Gazit and P. Madhusudan and Martin, {Milo M. K.} and Mukund Raghothaman and Shamwaditya Saha and Seshia, {Sanjit A.} and Rishabh Singh and Armando Solar-Lezama and Emina Torlak and Abhishek Udupa",

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doi = "10.3233/978-1-61499-495-4-1",

language = "English",

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Alur, R, Bodik, R, Dallal, E, Fisman, D, Garg, P, Juniwal, G, Kress-Gazit, H, Madhusudan, P, Martin, MMK, Raghothaman, M, Saha, S, Seshia, SA, Singh, R, Solar-Lezama, A, Torlak, E & Udupa, A 2015, Syntax-Guided Synthesis. in M Irlbeck & D Peled (eds), Dependable Software Systems Engineering. Nato Science for Peace and Security Series D-Information and Communication Security, IOS Press, pp. 1-25. https://doi.org/10.3233/978-1-61499-495-4-1

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AU - Alur, Rajeev

AU - Bodik, Rastislav

AU - Dallal, Eric

AU - Fisman, Dana

AU - Garg, Pranav

AU - Juniwal, Garvit

AU - Kress-Gazit, Hadas

AU - Madhusudan, P.

AU - Martin, Milo M. K.

AU - Raghothaman, Mukund

AU - Saha, Shamwaditya

AU - Seshia, Sanjit A.

AU - Singh, Rishabh

AU - Solar-Lezama, Armando

AU - Torlak, Emina

AU - Udupa, Abhishek

PY - 2015

Y1 - 2015

N2 - The classical formulation of the program-synthesis problem is to find aprogram that meets a correctness specification given as a logical formula. Recent work on program synthesis and program optimization illustrates many potential benefits of allowing the user to supplement the logical specification with a syntactic template that constrains the space of allowed implementations. Our goal is to identify the core computational problem common to these proposals in a logical framework. The input to the syntax-guided synthesis problem (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 so that it satisfies the specification in the given theory. We describe alternative solution strategies that combine learning, counter example analysis and constraint solving. We report on prototype implementations, and present experimental results on the set of benchmarks collected as part of thefirst SyGuS-Comp competition held in July 2014.

AB - The classical formulation of the program-synthesis problem is to find aprogram that meets a correctness specification given as a logical formula. Recent work on program synthesis and program optimization illustrates many potential benefits of allowing the user to supplement the logical specification with a syntactic template that constrains the space of allowed implementations. Our goal is to identify the core computational problem common to these proposals in a logical framework. The input to the syntax-guided synthesis problem (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 so that it satisfies the specification in the given theory. We describe alternative solution strategies that combine learning, counter example analysis and constraint solving. We report on prototype implementations, and present experimental results on the set of benchmarks collected as part of thefirst SyGuS-Comp competition held in July 2014.

KW - Program Synthesis

KW - Constraint Solving

KW - Counterexamples

KW - Machine Learning

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BT - Dependable Software Systems Engineering

A2 - Irlbeck, Maximilian

A2 - Peled, Doron

PB - IOS Press

ER -

Syntax-Guided Synthesis

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