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| M. Doi, Y. Higo, R. Arima, K. Shimonaka, and S. Kusumoto, "On the Naturalness of Auto-Generated Code —Can We Identify Auto-Generated Code Automatically?—," In 26th IEEE/ACM International Conference on Program Comprehension (ICPC2018), pp. 340-343, May 2018. | |
| ID | 543 |
| 分類 | 国際会議 |
| タグ | auto-generated automatically?— code identify naturalness we —can |
| 表題 (title) |
On the Naturalness of Auto-Generated Code —Can We Identify Auto-Generated Code Automatically?— |
| 表題 (英文) |
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| 著者名 (author) |
Masayuki Doi,Yoshiki Higo,Ryo Arima,Kento Shimonaka,Shinji Kusumoto |
| 英文著者名 (author) |
Masayuki Doi,Yoshiki Higo,Ryo Arima,Kento Shimonaka,Shinji Kusumoto |
| 編者名 (editor) |
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| 編者名 (英文) |
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| キー (key) |
Masayuki Doi,Yoshiki Higo,Ryo Arima,Kento Shimonaka,Shinji Kusumoto |
| 書籍・会議録表題 (booktitle) |
26th IEEE/ACM International Conference on Program Comprehension (ICPC2018) |
| 書籍・会議録表題(英文) |
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| 巻数 (volume) |
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| 号数 (number) |
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| ページ範囲 (pages) |
340-343 |
| 組織名 (organization) |
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| 出版元 (publisher) |
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| 出版元 (英文) |
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| 出版社住所 (address) |
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| 刊行月 (month) |
5 |
| 出版年 (year) |
2018 |
| 採択率 (acceptance) |
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| URL |
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| 付加情報 (note) |
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| 注釈 (annote) |
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| 内容梗概 (abstract) |
Recently, a variety of studies have been conducted on source code analysis. If auto-generated code is included in the target source code, it is usually removed in a preprocessing phase because the presence of auto-generated code may have negative effects on source code analysis. A straightforward way to remove autogenerated code is searching special comments that are included in the files of auto-generated code. However, it becomes impossible to identify auto-generated code with the way if such special comments have disappeared for some reasons. It is obvious that it takes too much effort to see source files one by one manually. In this paper, we propose a new technique to identify auto-generated code by using the naturalness of auto-generated code.We used a golden set that includes thousands of hand-made source files and source files generated by four kinds of compiler-compilers. Through the evaluation with the dataset, we confirmed that our technique was able to identify auto-generated code with over 99% precision and recall for all the cases. |
| 論文電子ファイル | camera_ready.pdf (application/pdf) [一般閲覧可] |
| BiBTeXエントリ |
@inproceedings{id543,
title = {On the Naturalness of Auto-generated Code —Can We Identify Auto-Generated Code Automatically?—},
author = {Masayuki Doi and Yoshiki Higo and Ryo Arima and Kento Shimonaka and Shinji Kusumoto},
booktitle = {26th IEEE/ACM International Conference on Program Comprehension (ICPC2018)},
pages = {340-343},
month = {5},
year = {2018},
}
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