Date of Submission
Spring 2020
Academic Program
Computer Science
Project Advisor 1
Sven Anderson
Abstract/Artist's Statement
Programmers tend to split their code into multiple files or sub-modules. When a program is executed, these sub-modules interact to produce the desired effect. One can, therefore, represent programs with graphs, where each node corresponds to some file and each edge corresponds to some relationship between files, such as two files being located in the same package or one file importing the content of another. This project trains Graph Neural Networks on such graphs to learn to predict future imports in Java programs and shows that Graph Neural Networks outperform various baseline methods by a wide margin.
Open Access Agreement
Open Access
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Fedchin, Aleksandr, "Predicting Imports in Java Code with Graph Neural Networks" (2020). Senior Projects Spring 2020. 300.
https://digitalcommons.bard.edu/senproj_s2020/300
This work is protected by a Creative Commons license. Any use not permitted under that license is prohibited.