Presentation 2022-03-07
Project-domain adaptation with RoBERTa Model for Code Completion
Daisuke Fukumoto, Toshiki Hirao, Kenji Fujiwara, Hajimu Iida,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) Code completion is a function that automatically recommends code for developers when they are writing code. Code completion can reduce coding time even for developers with insufficient skills. In the previous research, the machine learning-based completion that considers the context of the program and completes tokens in a more generally has been proposed. However, these previous studies have reported that the accuracy of completion decreases rapidly when the number of completing tokens increases. In this study, we propose a method that additionally trains RoBERTa, a machine learning model for natural language processing, on a dataset built in the domain of a developer's repository. We expect it can reduce the vocabulary recommended by the model and improve the completion accuracy. As a result of our experiments, we confirmed a improvement in accuracy compared to pre-trained model.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Code Completion / Transfer Learning / BERT / RoBERTa
Paper # SS2021-50
Date of Issue 2022-02-28 (SS)

Conference Information
Committee SS
Conference Date 2022/3/7(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English) Software Science etc.
Chair Takashi Kobayashi(Tokyo Inst. of Tech.)
Vice Chair Kozo Okano(Shinshu Univ.)
Secretary Kozo Okano(Hiroshima City Univ.)
Assistant Shinpei Ogata(Shinshu Univ.)

Paper Information
Registration To Technical Committee on Software Science
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Project-domain adaptation with RoBERTa Model for Code Completion
Sub Title (in English)
Keyword(1) Code Completion
Keyword(2) Transfer Learning
Keyword(3) BERT
Keyword(4) RoBERTa
1st Author's Name Daisuke Fukumoto
1st Author's Affiliation Nara Institute of Science and Technology(NAIST)
2nd Author's Name Toshiki Hirao
2nd Author's Affiliation Nara Institute of Science and Technology(NAIST)
3rd Author's Name Kenji Fujiwara
3rd Author's Affiliation Tokyo City University(TCU)
4th Author's Name Hajimu Iida
4th Author's Affiliation Nara Institute of Science and Technology(NAIST)
Date 2022-03-07
Paper # SS2021-50
Volume (vol) vol.121
Number (no) SS-416
Page pp.pp.49-53(SS),
#Pages 5
Date of Issue 2022-02-28 (SS)