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L-CMP: an automatic learning-based parameterized verification tool

Jialun Cao, Yongjian Li, Jun Pang

Abstract

This demo introduces L-CMP, an automatic learning-based parameterized verification tool. It can verify parameterized protocols by combining machine learning and model checking techniques. Given a parameterized protocol, L-CMP learns a set of auxiliary invariants and implements verification of the protocol using the invariants automatically. In particular, the learned auxiliary invariants are straightforward and readable. The experimental results show that L-CMP can successfully verify a number of cache coherence protocols, including the industrial-scale FLASH protocol. The video is available at https://youtu.be/6Dl2HiiiS4E, and L-CMPL-CMP can be downloaded at https://github.com/ ArabelaTso/Learning-Based-ParaVerifer.

BibTeX
@inproceedings{Cao-al:ASE18,
  author    = {Jialun Cao and
               Yongjian Li and
               Jun Pang},
  title     = {{L-CMP:} an automatic learning-based parameterized verification tool},
  booktitle = {ASE},
  pages     = {892--895},
  publisher = {{ACM}},
  year      = {2018},
}

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