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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 7 of 7  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
KBSE 2024-03-15
14:50
Okinawa Okinawa Prefectual General Welfare Center
(Primary: On-site, Secondary: Online)
Learning data creation support tool for learning program defects using images
Kazuhiko Ogawa, Takako Nakatani (OUJ) KBSE2023-89
We have developed CNN-BI system that learns and infers defects from the images of programs. This paper introduces a tool... [more] KBSE2023-89
pp.132-137
KBSE, SC 2023-11-18
15:10
Miyagi Sento Kaikan Research to improve the accuracy of inferring program defects using deep learning
Kazuhiko Ogawa, Takako Nakatani (OUJ) KBSE2023-50 SC2023-33
Experienced developers seem to be able to identify defects in programs created by beginners at a glance.
We applied sup... [more]
KBSE2023-50 SC2023-33
pp.93-98
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
 Results 1 - 7 of 7  /   
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