Web: http://arxiv.org/abs/2206.08713

June 20, 2022, 1:10 a.m. | Ilya Utkin, Egor Spirin, Egor Bogomolov, Timofey Bryksin

cs.LG updates on arXiv.org arxiv.org

As researchers and practitioners apply Machine Learning to increasingly more
software engineering problems, the approaches they use become more
sophisticated. A lot of modern approaches utilize internal code structure in
the form of an abstract syntax tree (AST) or its extensions: path-based
representation, complex graph combining AST with additional edges. Even though
the process of extracting ASTs from code can be done with different parsers,
the impact of choosing a parser on the final model quality remains unstudied.
Moreover, researchers …

arxiv code impact models on

More from arxiv.org / cs.LG updates on arXiv.org

Machine Learning Researcher - Saalfeld Lab

@ Howard Hughes Medical Institute - Chevy Chase, MD | Ashburn, Virginia

Project Director, Machine Learning in US Health

@ ideas42.org | Remote, US

Data Science Intern

@ NannyML | Remote

Machine Learning Engineer NLP/Speech

@ Play.ht | Remote

Research Scientist, 3D Reconstruction

@ Yembo | Remote, US

Clinical Assistant or Associate Professor of Management Science and Systems

@ University at Buffalo | Buffalo, NY