Kusumoto Laboratory: K. Hanayama, S. Matsumoto, and S. Kusumoto, Humpback: Code Completion System for Dockerfiles Based on Language Models, December 2020.
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K. Hanayama, S. Matsumoto, and S. Kusumoto, "Humpback: Code Completion System for Dockerfiles Based on Language Models," In 1st Workshop on Natural Language Processing Advancements for Software Engineering (NLPaSE 2020), pp. 1-4, December 2020.
ID 674
分類 国際会議
タグ code completion dockerfiles humpback language models system
表題 (title) Humpback: Code Completion System for Dockerfiles Based on Language Models
表題 (英文)
著者名 (author) Kaisei Hanayama,Shinsuke Matsumoto,Shinji Kusumoto
英文著者名 (author) Kaisei Hanayama,Shinsuke Matsumoto,Shinji Kusumoto
編者名 (editor)
編者名 (英文)
キー (key) Kaisei Hanayama,Shinsuke Matsumoto,Shinji Kusumoto
書籍・会議録表題 (booktitle) 1st Workshop on Natural Language Processing Advancements for Software Engineering (NLPaSE 2020)
書籍・会議録表題(英文)
巻数 (volume)
号数 (number)
ページ範囲 (pages) 1-4
組織名 (organization)
出版元 (publisher)
出版元 (英文)
出版社住所 (address)
刊行月 (month) 12
出版年 (year) 2020
採択率 (acceptance)
URL
付加情報 (note)
注釈 (annote)
内容梗概 (abstract) The object of this study is Docker, the de facto standard containerization platform. Containers in Docker are built by creating files called Dockerfiles. Managing the infrastructure as code makes it possible to incorporate knowledge gained from conventional software development. However, infrastructure as code is a relatively new technology, some domains of which have not been fully researched. In this study, we focus on code completion and aim to construct a system that supports the development of Dockerfiles. The proposed code completion system, Humpback, applies machine learning to a pre-collected dataset with long short-term memory to create language models and uses model switching to overcome a Docker-specific code completion problem. Evaluation experiments show that Humpback has a high average accuracy of 96.9%.
論文電子ファイル k-hanaym_202012_nlpase (application/pdf) [一般閲覧可]
BiBTeXエントリ
@inproceedings{id674,
         title = {Humpback: Code Completion System for Dockerfiles Based on Language Models},
        author = {Kaisei Hanayama and Shinsuke Matsumoto and Shinji Kusumoto},
     booktitle = {1st Workshop on Natural Language Processing Advancements for Software Engineering (NLPaSE 2020)},
         pages = {1-4},
         month = {12},
          year = {2020},
}
  

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