Program synthesis from polymorphic refinement types
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Solar-Lezama_Program synthesis.pdf
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475.81 KB
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Author(s)
Polikarpova, Nadezhda
Kuraj, Ivan
Solar Lezama, Armando
Date Issued
June 2016
Journal
Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation - PLDI 2016
Publisher
Association for Computing Machinery
Citation
Polikarpova, Nadia, Ivan Kuraj, and Armando Solar-Lezama. "Program Synthesis from Polymorphic Refinement Types." Proceedings of the 37th ACM SIGPLAN Conference on Programming Language Design and Implementation PLDI '16, 13-17 June, 2016, Santa Barbara, CA, ACM Press, 2016, pp. 522–38.
Version
Original manuscript
Abstract
We present a method for synthesizing recursive functions that provably satisfy a given specification in the form of a polymorphic refinement type. We observe that such specifications are particularly suitable for program synthesis for two reasons. First, they offer a unique combination of expressive power and decidability, which enables automatic verification—and hence synthesis—of nontrivial programs. Second, a type-based specification for a program can often be effectively decomposed into independent specifications for its components, causing the synthesizer to consider fewer component combinations and leading to a combinatorial reduction in the size of the search space. At the core of our synthesis procedure is a newalgorithm for refinement type checking, which supports specification decomposition. We have evaluated our prototype implementation on a large set of synthesis problems and found that it exceeds the state of the art in terms of both scalability and usability. The tool was able to synthesize more complex programs than those reported in prior work (several sorting algorithms and operations on balanced search trees), as well as most of the benchmarks tackled by existing synthesizers, often starting from a more concise and intuitive user input.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1145/2908080.2908093
