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Software development support using source code corpus

Research Project

Project/Area Number 15K00108
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Software
Research InstitutionNihon University

Principal Investigator

YAMAMOTO Tetsuo  日本大学, 工学部, 准教授 (40388129)

Project Period (FY) 2015-04-01 – 2018-03-31
Project Status Completed (Fiscal Year 2017)
Budget Amount *help
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2016: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2015: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
Keywordsコード補完 / コード推薦 / RNN / ソースコード推薦 / 機械学習
Outline of Final Research Achievements

Developers reuse existing source code or use libraries to develop effectively. In this study, we focus on the order of method invocation statements in existing source code and propose to suggest method invocation statements. This study proposed an approach to suggest method invocation statements using recurrent neural network. I have implemented the approach and conducted experiments to measure an accuracy with 10 open source software projects. I have investigated various parameters of recurrent neural network. This evaluation has shown that our approach is 38% accuracy in API code suggestion, it can correctly suggest the API with top 1 candidate.

Report

(4 results)
  • 2017 Annual Research Report   Final Research Report ( PDF )
  • 2016 Research-status Report
  • 2015 Research-status Report
  • Research Products

    (5 results)

All 2017 2016

All Journal Article (2 results) (of which Peer Reviewed: 2 results) Presentation (3 results)

  • [Journal Article] 回帰結合ニューラルネットワークを利用したAPI推薦手法2017

    • Author(s)
      山本哲男
    • Journal Title

      情報処理学会論文誌

      Volume: 58 Pages: 769-779

    • NAID

      170000173374

    • Related Report
      2017 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Code Suggestion of Method Call Statements Using a Source Code Corpus2017

    • Author(s)
      Yamamoto Tetsuo
    • Journal Title

      Proceedings of 2017 24th Asia-Pacific Software Engineering Conference (APSEC2017)

      Volume: 1 Pages: 666-671

    • DOI

      10.1109/apsec.2017.82

    • Related Report
      2017 Annual Research Report
    • Peer Reviewed
  • [Presentation] 分散表現ベクトルを用いたソースコード検索及び分類の検討2017

    • Author(s)
      山本哲男
    • Organizer
      電子情報通信学会技術研究報告(ソフトウェアサイエンス研究会)
    • Place of Presentation
      てんぶす那覇
    • Related Report
      2016 Research-status Report
  • [Presentation] 機械学習を利用したソースコード補完手法2016

    • Author(s)
      山本哲男
    • Organizer
      電子情報通信学会技術研究報告
    • Place of Presentation
      沖縄県立宮古青少年の家
    • Year and Date
      2016-03-10
    • Related Report
      2015 Research-status Report
  • [Presentation] 回帰結合ニューラルネットワークを利用したAPI推薦手法2016

    • Author(s)
      山本哲男
    • Organizer
      ソフトウェアエンジニアリングシンポジウム2016
    • Place of Presentation
      東洋大学 白山キャンパス
    • Related Report
      2016 Research-status Report

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Published: 2015-04-16   Modified: 2019-03-29  

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