FuSeBMC AI: Acceleration of Hybrid Approach through Machine Learning

We present FuSeBMC-AI, a test generation tool grounded in machine learning techniques. FuSeBMC-AI extracts various features from the program and employs support vector machine and neural network models to predict a hybrid approach optimal configuration. FuSeBMC-AI utilizes Bounded Model Checking and...

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Bibliographic Details
Published in:arXiv.org 2024-04
Main Authors: Alshmrany, Kaled M, Aldughaim, Mohannad, Wei, Chenfeng, Sweet, Tom, Allmendinger, Richard, Cordeiro, Lucas C
Format: Article
Language:English
Subjects:
Configurations
Machine learning
Neural networks
Support vector machines
Verification
Online Access:Get full text
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Summary:We present FuSeBMC-AI, a test generation tool grounded in machine learning techniques. FuSeBMC-AI extracts various features from the program and employs support vector machine and neural network models to predict a hybrid approach optimal configuration. FuSeBMC-AI utilizes Bounded Model Checking and Fuzzing as back-end verification engines. FuSeBMC-AI outperforms the default configuration of the underlying verification engine in certain cases while concurrently diminishing resource consumption.
ISSN:2331-8422