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Paper Abstract and Keywords
Presentation 2026-03-03 13:55
Leveraging Development History to Improve Self-Admitted Technical Debt Detection
Hitomi Taniguchi, Tetsuo Yamamoto (Ryukoku Univ.) SS2025-49
Abstract (in Japanese) (See Japanese page) 
(in English) This study aims to improve the detection accuracy of Self-Admitted Technical Debt (SATD) by proposing a new detection method that leverages Commit history.
While conventional SATD detection methods primarily classify based on comment text, their accuracy can decrease for ambiguous, context-dependent comments. To address this, our method utilizes diff information from the development history at the time of SATD introduction. We employ CodeBERT, a pre-trained model, using input features that combine textual information with these historical diffs.
To evaluate the proposed method, we conducted experiments using an existing SATD dataset and compared the results with a baseline method using only textual information. The evaluation results indicate that the proposed method outperforms the baseline, demonstrating the effectiveness of incorporating development history information.
Keyword (in Japanese) (See Japanese page) 
(in English) Self-Admitted Technical Debt / Technical Debt / Commit History / Machine Learning / CodeBERT / Git / /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 376, SS2025-49, pp. 115-120, March 2026.
Paper # SS2025-49 
Date of Issue 2026-02-23 (SS) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 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)
Download PDF SS2025-49

Conference Information
Committee SS  
Conference Date 2026-03-02 - 2026-03-04 
Place (in Japanese) (See Japanese page) 
Place (in English) Tsushimashi Koryu Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SS 
Conference Code 2026-03-SS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Leveraging Development History to Improve Self-Admitted Technical Debt Detection 
Sub Title (in English)  
Keyword(1) Self-Admitted Technical Debt  
Keyword(2) Technical Debt  
Keyword(3) Commit History  
Keyword(4) Machine Learning  
Keyword(5) CodeBERT  
Keyword(6) Git  
Keyword(7)  
Keyword(8)  
1st Author's Name Hitomi Taniguchi  
1st Author's Affiliation Ryukoku University (Ryukoku Univ.)
2nd Author's Name Tetsuo Yamamoto  
2nd Author's Affiliation Ryukoku University (Ryukoku Univ.)
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Speaker Author-1 
Date Time 2026-03-03 13:55:00 
Presentation Time 25 minutes 
Registration for SS 
Paper # SS2025-49 
Volume (vol) vol.125 
Number (no) no.376 
Page pp.115-120 
#Pages 6 
Date of Issue 2026-02-23 (SS) 

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