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Paper Abstract and Keywords
Presentation 2008-05-29 15:15
Identifying Fault-Prone Tokens in Source Code Modules with Spam-Filtering Technique
Ryosuke Morii, Osamu Mizuno, Tohru Kikuno (Osaka Univ.) SS2008-4 KBSE2008-4
Abstract (in Japanese) (See Japanese page) 
(in English) Prediction of fault-prone(FP) software modules has been one of the important area of software testing and many approaches has been conducted.Most of them use software metrics for predection, however there is difficulties in collecting the metrics.We introduced a new approach, named "Fault-Prone Filtering".In this approach, FP modules are detected in a way that the source code modules are regarded as text files and they are classified by text mining technique based on Bayesian theory, so there is no need to collect the metrics.
But there was an implementing shortage of this approach at this time.When we classified modules into FP or NFP(not-fault-prone), we could get the result of classification only.There was no information available on FP tokens in each module, and such information is important to conduct debug activities.
In this paper, we tried to develop a tool that classifies not only modules into FP or NFP but also tokens in them.And we experimented using open source project to check how accurately this tool classified tokens.
Keyword (in Japanese) (See Japanese page) 
(in English) Fault-prone Module / text mining / Bayesian theory / / / / /  
Reference Info. IEICE Tech. Rep., vol. 108, no. 64, SS2008-4, pp. 19-24, May 2008.
Paper # SS2008-4 
Date of Issue 2008-05-22 (SS, KBSE) 
ISSN Print edition: ISSN 0913-5685    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)
Download PDF SS2008-4 KBSE2008-4

Conference Information
Committee KBSE SS  
Conference Date 2008-05-29 - 2008-05-30 
Place (in Japanese) (See Japanese page) 
Place (in English) Miyazaki Citizens' Plaza 
Topics (in Japanese) (See Japanese page) 
Topics (in English) general 
Paper Information
Registration To SS 
Conference Code 2008-05-KBSE-SS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Identifying Fault-Prone Tokens in Source Code Modules with Spam-Filtering Technique 
Sub Title (in English)  
Keyword(1) Fault-prone Module  
Keyword(2) text mining  
Keyword(3) Bayesian theory  
1st Author's Name Ryosuke Morii  
1st Author's Affiliation Osaka University (Osaka Univ.)
2nd Author's Name Osamu Mizuno  
2nd Author's Affiliation Osaka University (Osaka Univ.)
3rd Author's Name Tohru Kikuno  
3rd Author's Affiliation Osaka University (Osaka Univ.)
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Speaker Author-1 
Date Time 2008-05-29 15:15:00 
Presentation Time 30 minutes 
Registration for SS 
Paper # SS2008-4, KBSE2008-4 
Volume (vol) vol.108 
Number (no) no.64(SS), no.65(KBSE) 
Page pp.19-24 
Date of Issue 2008-05-22 (SS, KBSE) 

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