FuSeBMC AI: Acceleration of Hybrid Approach through Machine Learning

• URL: http://arxiv.org/abs/2404.06031v1
• Date: Tue, 9 Apr 2024 05:34:19 GMT
• Title: FuSeBMC AI: Acceleration of Hybrid Approach through Machine Learning
• Authors: Kaled M. Alshmrany, Mohannad Aldughaim, Chenfeng Wei, Tom Sweet, Richard Allmendinger, Lucas C. Cordeiro,
• Abstract summary: FuSeBMC-AI is 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.
• Score: 3.2815052047959874
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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