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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
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Committee Date Time Place Paper Title / Authors Abstract Paper #
KBSE 2023-01-20
13:00		 Ishikawa  
(Primary: On-site, Secondary: Online)		 A study for using deep learning inference results of program defects in code review checklists
Kazuhiko Ogawa, Takako Nakatani (OUJ) KBSE2022-51		 In system development, various efforts are made to improve the quality of programs.
One of these efforts is code review... [more]		 KBSE2022-51
pp.46-51
KBSE 2022-03-09
16:20		 Online Online (Zoom) Code review support and verification of effectiveness using deep learning with images of programs
Kazuhiko Ogawa, Takako Nakatani (OUJ) KBSE2021-49		 Code review is one of the ways to improve the quality of programs.
Code reviews cannot point out all faults, but if rev... [more]		 KBSE2021-49
pp.48-53
KBSE, IPSJ-SE, SS [detail] 2021-07-08
14:50		 Online Online (Zoom) Research for using image analysis of program fault by deep learning for code review.
Kazuhiko Ogawa, Takako Nakatani (OUJ) SS2021-6 KBSE2021-18		 In order to predict the location of faults in a program, we imaged the source code of the defective program and verified... [more] SS2021-6 KBSE2021-18
pp.31-36
KBSE 2021-03-06
13:40		 Online Online Research for finding faults in Programs using object detection algorithm by CNN-BI system
Kazuhiko Ogawa, Takako Nakatani (OUJ) KBSE2020-45		 In order to predict the location of program faults, we generated images the source code of a faulty program and trained ... [more] KBSE2020-45
pp.65-70
KBSE 2020-03-07
13:30		 Okinawa Tenbusu-Naha
(Cancelled but technical report was issued)		 Research for improving the accuracy of program fault detection by CNN-BI system
Kazuhiko Ogawa, Takako Nakatani (OUJ) KBSE2019-58		 Many researchers have done much research to improve software quality.One way to improve the quality of a program is to i... [more] KBSE2019-58
pp.73-78
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