Software Open Access
Padhi, Saswat; Millstein, Todd; Nori, Aditya; Sharma, Rahul
Abstract:
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 5x mean speedup.
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The Artifact:
This software artifact contains all 180 invariant-inference SyGuS benchmarks, implementations of all 6 grammars presented in our paper, working code for the hybrid enumeration (HEnum
) technique, and several scripts to reproduce the empirical claims made in the paper:
PLearn
and HEnum
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Instructions:
cav19-artifact-100.zip
file.sha1sum
of the zip file matches with cav19-artifact-100.sha1
:
cav19-artifact-100.zip
and cav19-artifact-100.sha1
files to the same directory.sha1sum -c cav19-artifact-100.sha1
.cav19-artifact-100.zip: OK
.CAV19_Artifact_100.ova
VM image,Getting_Started.md
), andInstructions.html
).virtualbox
on your machine..ova
image to your virtualbox.cav
and password ae.
CTRL+ALT+T
) and try:
cd CAV_100
make clean ; make dependencies
Everything built!
message, then you can proceed with the artifact evaluation steps.Name | Size | |
---|---|---|
cav19-artifact-100.sha1
md5:a28d8c49bb091ab4e389d076db8e134c |
65 Bytes | Download |
cav19-artifact-100.zip
md5:1d5e0da8e4f595271affb5887ae523e3 |
5.2 GB | Download |
All versions | This version | |
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Views | 179 | 179 |
Downloads | 34 | 34 |
Data volume | 109.6 GB | 109.6 GB |
Unique views | 152 | 152 |
Unique downloads | 21 | 21 |