Overfitting in Synthesis: Theory and Practice (Extended Version) Article Swipe
Saswat Padhi
,
Todd Millstein
,
Aditya V. Nori
,
Rahul Sharma
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1905.07457
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1905.07457
In syntax-guided synthesis (SyGuS), a synthesizer's goal is to automatically generate a program belonging to a grammar of possible implementations that meets a logical specification. We investigate a common limitation across state-of-the-art SyGuS tools that perform counterexample-guided inductive synthesis (CEGIS). We empirically observe that as the expressiveness of the provided grammar increases, the performance of these tools degrades significantly. We claim that this degradation is not only due to a larger search space, but also due to overfitting. We formally define this phenomenon and prove no-free-lunch theorems for SyGuS, which reveal a fundamental tradeoff between synthesizer performance and grammar expressiveness. A standard approach to mitigate overfitting in machine learning is to run multiple learners with varying expressiveness in parallel. We demonstrate that this insight can immediately benefit existing SyGuS tools. We also propose a novel single-threaded technique called hybrid enumeration that interleaves different grammars and outperforms the winner of the 2018 SyGuS competition (Inv track), solving more problems and achieving a $5\times$ mean speedup.
Related Topics
Concepts
Overfitting
Computer science
Speedup
Correctness
Programmer
Syntax
Grammar
Programming language
Rule-based machine translation
Counterexample
Artificial intelligence
Toolchain
Theoretical computer science
Parallel computing
Mathematics
Artificial neural network
Discrete mathematics
Philosophy
Software
Linguistics
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/1905.07457
- https://arxiv.org/pdf/1905.07457
- OA Status
- green
- Cited By
- 1
- References
- 23
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2945622290
All OpenAlex metadata
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https://doi.org/10.48550/arxiv.1905.07457Digital Object Identifier
- Title
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Overfitting in Synthesis: Theory and Practice (Extended Version)Work title
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preprintOpenAlex work type
- Language
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enPrimary language
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2019Year of publication
- Publication date
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2019-05-17Full publication date if available
- Authors
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Saswat Padhi, Todd Millstein, Aditya V. Nori, Rahul SharmaList of authors in order
- Landing page
-
https://arxiv.org/abs/1905.07457Publisher landing page
- PDF URL
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https://arxiv.org/pdf/1905.07457Direct link to full text PDF
- Open access
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/1905.07457Direct OA link when available
- Concepts
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Overfitting, Computer science, Speedup, Correctness, Programmer, Syntax, Grammar, Programming language, Rule-based machine translation, Counterexample, Artificial intelligence, Toolchain, Theoretical computer science, Parallel computing, Mathematics, Artificial neural network, Discrete mathematics, Philosophy, Software, LinguisticsTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2019: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| publication_date | 2019-05-17 |
| publication_year | 2019 |
| referenced_works | https://openalex.org/W607505555, https://openalex.org/W2796244040, https://openalex.org/W2550471858, https://openalex.org/W2843529596, https://openalex.org/W1858945639, https://openalex.org/W2132661148, https://openalex.org/W2156590219, https://openalex.org/W2142481893, https://openalex.org/W2798628553, https://openalex.org/W2938468157, https://openalex.org/W2898750165, https://openalex.org/W2113489899, https://openalex.org/W1966242183, https://openalex.org/W2134734244, https://openalex.org/W3102469351, https://openalex.org/W1534477342, https://openalex.org/W2121415300, https://openalex.org/W2416392025, https://openalex.org/W2013596093, https://openalex.org/W258469679, https://openalex.org/W993487908, https://openalex.org/W1965446936, https://openalex.org/W2901330051 |
| referenced_works_count | 23 |
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| sustainable_development_goals[0].score | 0.5600000023841858 |
| sustainable_development_goals[0].display_name | Quality Education |
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