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Paper Abstract and Keywords
Presentation 2022-03-07 16:45
Performance Evaluation of Defect Prediction using Trace Logs
Issei Morita, Yutaro Kashiwa, Tsukasa Nakamura, Hiroki Yamamoto, Masanari Kondo, Yasutaka Kamei, Naoyasu Ubayashi (Kyushu Univ.) SS2021-53
Abstract (in Japanese) (See Japanese page) 
(in English) In order to detect defects at an early stage of software development, techniques for predicting whether or not a change made to software contains a defect have been widely studied. In the vast majority of cases, static information (i.e., information that does not require program execution) is used to develop change-level defect prediction models. Dynamic information on the other hand (i.e., trace logs) is seldom used. It was hypothesized that trace logs could capture changes in the behavior of software and result in the improved performance of defect prediction models. In this study, we introduced several new types of
metrics using the differences made by trace logs before and after a change, and then built a prediction model based on these. As a result of experiments using an OSS project, we demonstrated that our proposed dynamic metrics partially improve the defect prediction performance compared to using only static metrics.
Keyword (in Japanese) (See Japanese page) 
(in English) Defect Prediction / Dynamic Analysis / Trace Logs / / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 416, SS2021-53, pp. 66-71, March 2022.
Paper # SS2021-53 
Date of Issue 2022-02-28 (SS) 
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)
Notes on Review This article is a technical report without peer review, and its polished version will be published elsewhere.
Download PDF SS2021-53

Conference Information
Committee SS  
Conference Date 2022-03-07 - 2022-03-08 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Software Science etc. 
Paper Information
Registration To SS 
Conference Code 2022-03-SS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Performance Evaluation of Defect Prediction using Trace Logs 
Sub Title (in English)  
Keyword(1) Defect Prediction  
Keyword(2) Dynamic Analysis  
Keyword(3) Trace Logs  
1st Author's Name Issei Morita  
1st Author's Affiliation Kyushu University (Kyushu Univ.)
2nd Author's Name Yutaro Kashiwa  
2nd Author's Affiliation Kyushu University (Kyushu Univ.)
3rd Author's Name Tsukasa Nakamura  
3rd Author's Affiliation Kyushu University (Kyushu Univ.)
4th Author's Name Hiroki Yamamoto  
4th Author's Affiliation Kyushu University (Kyushu Univ.)
5th Author's Name Masanari Kondo  
5th Author's Affiliation Kyushu University (Kyushu Univ.)
6th Author's Name Yasutaka Kamei  
6th Author's Affiliation Kyushu University (Kyushu Univ.)
7th Author's Name Naoyasu Ubayashi  
7th Author's Affiliation Kyushu University (Kyushu Univ.)
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Speaker Author-1 
Date Time 2022-03-07 16:45:00 
Presentation Time 25 minutes 
Registration for SS 
Paper # SS2021-53 
Volume (vol) vol.121 
Number (no) no.416 
Page pp.66-71 
Date of Issue 2022-02-28 (SS) 

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