Semantic-aware Source Code Modeling

Source code modeling represents a promising avenue for automating software development, such as code generation, bug repair, and program analysis. This research direction aims to train deep neural nets to learn the statistical predictability inherent in human-written programs to enhance developer productivity, code quality, and the overall software development life cycle.

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Published
2024-10-18
DOI
https://doi.org/10.1145/3691620.3695605
Primary Topic
Software Engineering Research
Type
article
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article

Semantic-aware Source Code Modeling

Yangruibo Ding
Software Engineering Research
article

Semantic-aware Source Code Modeling

Yangruibo Ding
article en

Abstract

Source code modeling represents a promising avenue for automating software development, such as code generation, bug repair, and program analysis. This research direction aims to train deep neural nets to learn the statistical predictability inherent in human-written programs to enhance developer productivity, code quality, and the overall software development life cycle.

Columbia University (US)
Openalex Percentile: Top 72%
Software Engineering Research
DOIOpen Access PDFOpenAlex
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Semantic-aware Source Code Modeling — Yangruibo Ding · (2024) | TGRS Research Map | TGRS