FuSeBMC AI: Acceleration of Hybrid Approach through Machine Learning
<|reference_start|>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 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.<|reference_end|>
@article{alshmrany2024fusebmc,
    title={FuSeBMC AI: Acceleration of Hybrid Approach through Machine Learning},
    author={Kaled M. Alshmrany, Mohannad Aldughaim, Chenfeng Wei, Tom Sweet,
  Richard Allmendinger, and Lucas C. Cordeiro},
    journal={arXiv preprint arXiv:2404.06031},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.06031},
    primaryClass={cs.CR}
}