| Presentation | 2023-01-20 A study for using deep learning inference results of program defects in code review checklists Kazuhiko Ogawa, Takako Nakatani, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In system development, various efforts are made to improve the quality of programs. One of these efforts is code review. We applied a system using deep learning, which we call the CNN-BI system, to infer program defects, and found that the accuracy (F value) of defects in SQL statements was 0.71. In this study, we created a checklist that includes the inference results of the CNN-BI system as checklist items. We examined the impact of the checklists with inference results. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | code review / checklist / convolutional nural network / deep learning / bug inference |
| Paper # | KBSE2022-51 |
| Date of Issue | 2023-01-12 (KBSE) |
| Conference Information | |
| Committee | KBSE |
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| Conference Date | 2023/1/19(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Takuya Saruwatari(NTT Data) |
| Vice Chair | Yoshinori Tanabe(Tsurumi Univ.) |
| Secretary | Yoshinori Tanabe(Osaka Inst. of Tech.) |
| Assistant | Yoshitaka Aoki(BIPROGY) / Hiroki Horita(Ibaraki Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Knowledge-Based Software Engineering |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A study for using deep learning inference results of program defects in code review checklists |
| Sub Title (in English) | |
| Keyword(1) | code review |
| Keyword(2) | checklist |
| Keyword(3) | convolutional nural network |
| Keyword(4) | deep learning |
| Keyword(5) | bug inference |
| 1st Author's Name | Kazuhiko Ogawa |
| 1st Author's Affiliation | The Open University Of Japan(OUJ) |
| 2nd Author's Name | Takako Nakatani |
| 2nd Author's Affiliation | The Open University Of Japan(OUJ) |
| Date | 2023-01-20 |
| Paper # | KBSE2022-51 |
| Volume (vol) | vol.122 |
| Number (no) | KBSE-345 |
| Page | pp.pp.46-51(KBSE), |
| #Pages | 6 |
| Date of Issue | 2023-01-12 (KBSE) |