Kusumoto Laboratory: Y. Tomida, Y. Higo, S. Matsumoto, and S. Kusumoto, Visualizing Code Genealogy: How Code Is Evolutionarily Fixed in Program Repair?, September 2019.
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Y. Tomida, Y. Higo, S. Matsumoto, and S. Kusumoto, "Visualizing Code Genealogy: How Code Is Evolutionarily Fixed in Program Repair?," In The seventh IEEE Working Conference on Software Visualization (VISSOFT), pp. 23-27, September 2019.
ID 608
分類 国際会議
タグ code evolutionarily fixed genealogy how is program repair? visualizing
表題 (title) Visualizing Code Genealogy: How Code Is Evolutionarily Fixed in Program Repair?
表題 (英文)
著者名 (author) Yuya Tomida,Yoshiki Higo,Shinsuke Matsumoto,Shinji Kusumoto
英文著者名 (author)
編者名 (editor)
編者名 (英文)
キー (key) Yuya Tomida,Yoshiki Higo,Shinsuke Matsumoto,Shinji Kusumoto
書籍・会議録表題 (booktitle) The seventh IEEE Working Conference on Software Visualization (VISSOFT)
書籍・会議録表題(英文)
巻数 (volume)
号数 (number)
ページ範囲 (pages) 23-27
組織名 (organization)
出版元 (publisher)
出版元 (英文)
出版社住所 (address)
刊行月 (month) 9
出版年 (year) 2019
採択率 (acceptance)
URL https://conferences.computer.org/icsme/2019/pdfs/VISSOFT2019-oiFVGCPeZjO7ag702zOM9/131GTwny13tBREaFZne0fw/5DrbknBND4TLMEFslYfmXp.pdf
付加情報 (note) Cleveland, Ohio USA
注釈 (annote)
内容梗概 (abstract) Automated program repair (in short, APR) techniques that utilize genetic algorithm (in short, GA) have a capability of repairing programs even if the programs require
multiple code fragments to be changed. Those techniques repeat program generation, program evaluation, and program selection until a generated program passes all given test cases. Those techniques occasionally generate a large number of programs before a repaired program is generated. Thus, it is difficult to understand how an input program is evolved in the loop processing of genetic algorithm. In this paper, we are inspired by genealogy and propose a new technique to visualize program evolution in the process of automated program repair. We have implemented the proposed technique as a software tool for kGenProg, which is one of GA-based APR tools. We evaluated the proposed technique with the developers of kGenProg. In the evaluation, the developers found latent issues in kGenProg’s processing and came up with new ideas to improve program generation. From those results, we conclude that our visualization is useful to understand program evolution in the APR process.
論文電子ファイル PID6045203.pdf (application/pdf) [一般閲覧可]
BiBTeXエントリ
@inproceedings{id608,
         title = {Visualizing Code Genealogy: How Code is Evolutionarily Fixed in Program Repair?},
        author = {Yuya Tomida and Yoshiki Higo and Shinsuke Matsumoto and Shinji Kusumoto},
     booktitle = {The seventh IEEE Working Conference on Software Visualization (VISSOFT)},
         pages = {23-27},
         month = {9},
          year = {2019},
          note = {Cleveland, Ohio USA},
}
  

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