Learning Developer-Code Contribution Relationship via Heterogeneous Graph Attention Network for Repositories Oriented Code Readability Assessment

project
Feb 2022

To improve the performance of code readability assessment and enhance the practicality of existing assessment approaches, we propose a repository-oriented code readability assessment method based on Heterogeneous Graph Attention Network (HAN) to learn developer-code contribution relationship.

  • Automatically assessing code readability is important for project maintenance and evolution. However, existing code readability research only focuses on single files' assessment. These studies fail to utilize developer-code contribution relationship, which refers to the valuable information underlying code files and their developers in the context of code repository.

    • Paper

    • PyTorch
    • JavaParser
    • Heterogeneous Graph Attention Network
    • HPC
    We use cookies and similar technologies to provide certain features, enhance the user experience and deliver content that is relevant to your interests. Depending on their purpose, analysis and marketing cookies may be used in addition to technically necessary cookies. By clicking on "Agree and continue", you declare your consent to the use of the aforementioned cookies. you can make detailed settings or revoke your consent (in part if necessary) with effect for the future. For further information, please refer to ourPrivacy Policy.
    SupportRSS

    Early to bed and early to rise, makes a man healthy, wealthy, and wise. ——Benjamin Franklin

    © 2023 Yuyang Wang's Site. Powered by React.js