Many software engineering activities include source code analysis such as quality assessment, refactoring, testing, and vulnerability detection. The advancements in machine learning techniques have encouraged software engineering researchers to apply these techniques to such software engineering activities. With this literature survey, we aim to summarize the current knowledge in the area of applied machine learning for source code analysis.

Inspired from ML4Code, this site is an effort to create a living documentation of the relevant literature. You may find the complete survey paper online. Please cite the paper as

@misc{Sharma2021,
    title={A Survey on Machine Learning Techniques for Source Code Analysis},
    author={Tushar Sharma and Maria Kechagia and Stefanos Georgiou and Rohit Tiwari and Federica
    Sarro},
    year={2021},
    eprint={2110.09610},
    archivePrefix={arXiv},
    primaryClass={cs.SE}
}