L-CMP: An Automatic Learning-Based Parameterized Verification Tool

被引:2
|
作者
Cao, Jialun [1 ,2 ]
Li, Yongjian [1 ]
Pang, Jun [3 ]
机构
[1] Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing, Peoples R China
[2] Univ Chinese Acad Sci, Beijing, Peoples R China
[3] Univ Luxembourg, Ctr Secur Reliabil & Trust, Fac Sci Technol & Commun & Interdisciplinary, Esch Sur Alzette, Luxembourg
关键词
Parameterized verification; model checking; association rule learning; machine learning;
D O I
10.1145/3238147.3240487
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
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.
引用
收藏
页码:892 / 895
页数:4
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