Overview of Deep Learning-Based Code Representation and Its Applications
The analysis and inference of program play an important role in software development, maintenance and migration. How to efficiently obtain high quality information from program code has become a hot research topic. In recent years, a large number of researchers have introduced the deep learning-base...
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| Format: | Article |
| Language: | zho |
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Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
2022-09-01
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| Series: | Jisuanji kexue yu tansuo |
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| Online Access: | http://fcst.ceaj.org/fileup/1673-9418/PDF/2110073.pdf |
| _version_ | 1811307525654446080 |
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| author | ZHANG Xiangping, LIU Jianxun |
| author_facet | ZHANG Xiangping, LIU Jianxun |
| author_sort | ZHANG Xiangping, LIU Jianxun |
| collection | DOAJ |
| description | The analysis and inference of program play an important role in software development, maintenance and migration. How to efficiently obtain high quality information from program code has become a hot research topic. In recent years, a large number of researchers have introduced the deep learning-based representation technology into the code analysis tasks. The deep learning model can automatically extract the implicit and useful features implicit in the source code, which can alleviate the dependence on the manual construct feature. This paper first introduces the background and basic concepts of code representation, and summarizes the recent research work on deep learning-based code representation learning from the perspective of code static information analysis. Furthermore, this paper introduces the application of code representation on three tasks, code clone detection, code search and code completion. Finally, it discusses the challenges of deep learning-based code representation and the possible research directions in this field. |
| first_indexed | 2024-04-13T09:05:51Z |
| format | Article |
| id | doaj.art-b51b63b5a827432bafff978d594533a0 |
| institution | Directory Open Access Journal |
| issn | 1673-9418 |
| language | zho |
| last_indexed | 2024-04-13T09:05:51Z |
| publishDate | 2022-09-01 |
| publisher | Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press |
| record_format | Article |
| series | Jisuanji kexue yu tansuo |
| spelling | doaj.art-b51b63b5a827432bafff978d594533a02022-12-22T02:52:59ZzhoJournal of Computer Engineering and Applications Beijing Co., Ltd., Science PressJisuanji kexue yu tansuo1673-94182022-09-011692011202910.3778/j.issn.1673-9418.2110073Overview of Deep Learning-Based Code Representation and Its ApplicationsZHANG Xiangping, LIU Jianxun01. Hunan Key Lab for Services Computing and Novel Software Technology, Hunan University of Science and Technology, Xiangtan, Hunan 411201, China;2. School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, Hunan 411201, ChinaThe analysis and inference of program play an important role in software development, maintenance and migration. How to efficiently obtain high quality information from program code has become a hot research topic. In recent years, a large number of researchers have introduced the deep learning-based representation technology into the code analysis tasks. The deep learning model can automatically extract the implicit and useful features implicit in the source code, which can alleviate the dependence on the manual construct feature. This paper first introduces the background and basic concepts of code representation, and summarizes the recent research work on deep learning-based code representation learning from the perspective of code static information analysis. Furthermore, this paper introduces the application of code representation on three tasks, code clone detection, code search and code completion. Finally, it discusses the challenges of deep learning-based code representation and the possible research directions in this field.http://fcst.ceaj.org/fileup/1673-9418/PDF/2110073.pdf|code representation|representation learning|software engineering|code analysis|deep learning |
| spellingShingle | ZHANG Xiangping, LIU Jianxun Overview of Deep Learning-Based Code Representation and Its Applications Jisuanji kexue yu tansuo |code representation|representation learning|software engineering|code analysis|deep learning |
| title | Overview of Deep Learning-Based Code Representation and Its Applications |
| title_full | Overview of Deep Learning-Based Code Representation and Its Applications |
| title_fullStr | Overview of Deep Learning-Based Code Representation and Its Applications |
| title_full_unstemmed | Overview of Deep Learning-Based Code Representation and Its Applications |
| title_short | Overview of Deep Learning-Based Code Representation and Its Applications |
| title_sort | overview of deep learning based code representation and its applications |
| topic | |code representation|representation learning|software engineering|code analysis|deep learning |
| url | http://fcst.ceaj.org/fileup/1673-9418/PDF/2110073.pdf |
| work_keys_str_mv | AT zhangxiangpingliujianxun overviewofdeeplearningbasedcoderepresentationanditsapplications |