Publication Details

PAC Learning-Based Verification and Model Synthesis

CHEN, Y.; HSIEH, C.; LENGÁL, O.; LII, T.; TSAI, M.; WANG, B.; WANG, F. PAC Learning-Based Verification and Model Synthesis. In Proceedings of the 38th International Conference on Software Engineering. Austin, TX: Association for Computing Machinery, 2016. p. 714-724. ISBN: 978-1-4503-3900-1.
Czech title
Verifikace a syntéza modelu založené na PAC učení
Type
conference paper
Language
English
Authors
URL
Keywords

model synthesis, PAC learning, finite automata, program verification

Abstract

We introduce a novel technique for verification and model synthesis of sequential programs. Our technique is based on learning an approximate regular model of the set of feasible paths in a program, and testing whether this model contains an incorrect behavior. Exact learning algorithms require checking equivalence between the model and the program, which is a difficult problem, in general undecidable. Our learning procedure is therefore based on the framework of probably approximately correct (PAC) learning, which uses sampling instead, and provides correctness guarantees expressed using the terms error probability and confidence. Besides the verification result, our procedure also outputs the model with the said correctness guarantees. Obtained preliminary experiments show encouraging results, in some cases even outperforming mature software verifiers.

Published
2016
Pages
714–724
Proceedings
Proceedings of the 38th International Conference on Software Engineering
ISBN
978-1-4503-3900-1
Publisher
Association for Computing Machinery
Place
Austin, TX
DOI
UT WoS
000406138600063
EID Scopus
BibTeX
@inproceedings{BUT130941,
  author="Yu-Fang {Chen} and Chiao {Hsieh} and Ondřej {Lengál} and Tsung-Ju {Lii} and Ming-Hsien {Tsai} and Bow-Yaw {Wang} and Farn {Wang}",
  title="PAC Learning-Based Verification and Model Synthesis",
  booktitle="Proceedings of the 38th International Conference on Software Engineering",
  year="2016",
  pages="714--724",
  publisher="Association for Computing Machinery",
  address="Austin, TX",
  doi="10.1145/2884781.2884860",
  isbn="978-1-4503-3900-1",
  url="http://dx.doi.org/10.1145/2884781.2884860"
}
Back to top