Learning Contract Invariants Using Reinforcement Learning-Reference-Cited by-同舟云学术

Learning Contract Invariants Using Reinforcement Learning

Published:2022-10-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering
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Author:

Liu Junrui¹^ORCID,Chen Yanju²^ORCID,Tan Bryan³^ORCID,Dillig Isil⁴^ORCID,Feng Yu⁵^ORCID

Affiliation:

1. University of California, Santa Barbara, USA and Veridise Inc., USA

2. University of California, Santa Barbara, United States and Veridise Inc., USA

3. Veridise Inc., USA

4. University of Texas at Austin, United States and Veridise Inc., USA

5. University of California, Santa Barbara, United States of America and Veridise Inc., USA

Funder

Google

NSF

DARPA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3551349.3556962

Reference30 articles.

1. Nikolaj Bjørner , Arie Gurfinkel , Ken McMillan , and Andrey Rybalchenko . 2015. Horn Clause Solvers for Program Verification . Springer International Publishing , Cham , 24–51. https://doi.org/10.1007/978-3-319-23534-9_2 10.1007/978-3-319-23534-9_2 Nikolaj Bjørner, Arie Gurfinkel, Ken McMillan, and Andrey Rybalchenko. 2015. Horn Clause Solvers for Program Verification. Springer International Publishing, Cham, 24–51. https://doi.org/10.1007/978-3-319-23534-9_2

2. Priyanka Bose , Dipanjan Das , Yanju Chen , Yu Feng , Christopher Kruegel , and Giovanni Vigna . 2022 . SAILFISH: Vetting Smart Contract State-Inconsistency Bugs in Seconds. In 43rd IEEE Symposium on Security and Privacy, S&P 2022 , San Francisco, US , May 22-26, 2022. IEEE. https://arxiv.org/abs/2104.08638 Priyanka Bose, Dipanjan Das, Yanju Chen, Yu Feng, Christopher Kruegel, and Giovanni Vigna. 2022. SAILFISH: Vetting Smart Contract State-Inconsistency Bugs in Seconds. In 43rd IEEE Symposium on Security and Privacy, S&P 2022, San Francisco, US, May 22-26, 2022. IEEE. https://arxiv.org/abs/2104.08638

3. Relational verification using reinforcement learning

4. Abstract interpretation

5. Inductive invariant generation via abductive inference

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