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Paper Abstract and Keywords
Presentation 2021-07-08 14:50
Research for using image analysis of program fault by deep learning for code review.
Kazuhiko Ogawa, Takako Nakatani (OUJ) SS2021-6 KBSE2021-18
Abstract (in Japanese) (See Japanese page) 
(in English) In order to predict the location of faults in a program, we imaged the source code of the defective program and verified whether we could find the defective part of the program by learning with deep learning.
We found that the descriptions of the programs that caused the defects had something in common in the appearance of the source code, and we thought that we could find the defects by applying CNN (Convolutional Neural Network), which is one of the deep learning methods.
In this paper, we compare the results of a code review of a program that uses the results of inference from a model learned by deep learning and a code review of a program that does not use the results of inference.
We will experiment to see whether the code review using the results of inference by deep learning can reduce the review time and detect more defects than the code review without the results of inference.
We will also verify whether it is possible to detect unknown faults.
Keyword (in Japanese) (See Japanese page) 
(in English) bug inference / convolutional nural network / image of source code / deep learning / code review / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 95, KBSE2021-18, pp. 31-36, July 2021.
Paper # KBSE2021-18 
Date of Issue 2021-07-01 (SS, KBSE) 
ISSN Online edition: ISSN 2432-6380
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee KBSE IPSJ-SE SS  
Conference Date 2021-07-08 - 2021-07-09 
Place (in Japanese) (See Japanese page) 
Place (in English) Online (Zoom) 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To KBSE 
Conference Code 2021-07-KBSE-SE-SS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Research for using image analysis of program fault by deep learning for code review. 
Sub Title (in English)  
Keyword(1) bug inference  
Keyword(2) convolutional nural network  
Keyword(3) image of source code  
Keyword(4) deep learning  
Keyword(5) code review  
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)
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Speaker Author-1 
Date Time 2021-07-08 14:50:00 
Presentation Time 25 minutes 
Registration for KBSE 
Paper # SS2021-6, KBSE2021-18 
Volume (vol) vol.121 
Number (no) no.94(SS), no.95(KBSE) 
Page pp.31-36 
Date of Issue 2021-07-01 (SS, KBSE) 

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