Article

Spam Filter Based Approach for Finding Fault-Prone Software Modules

Authors:

Osamu Mizuno,

Shiro Ikami,

Shuya Nakaichi,

Tohru KikunoAuthors Info & Claims

MSR '07: Proceedings of the Fourth International Workshop on Mining Software Repositories

Page 4

https://doi.org/10.1109/MSR.2007.29

Published: 20 May 2007 Publication History

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Abstract

Because of the increase of needs for spam e-mail detection, the spam filtering technique has been improved as a convenient and effective technique for text mining. We propose a novel approach to detect fault-prone modules in a way that the source code modules are considered as text files and are applied to the spam filter directly. In order to show the applicability of our approach, we conducted experimental applications using source code repositories of Java based open source developments. The result of experiments shows that our approach can classify more than 75% of software modules correctly.

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Cited By

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Halkidi MSpinellis DTsatsaronis GVazirgiannis M(2018)Data mining in software engineeringIntelligent Data Analysis10.5555/2010978.201098715:3(413-441)Online publication date: 27-Dec-2018
https://dl.acm.org/doi/10.5555/2010978.2010987
Kaur IBajpai N(2016)An Empirical Study on Fault Prediction using Token-Based ApproachProceedings of the International Conference on Advances in Information Communication Technology & Computing10.1145/2979779.2979811(1-7)Online publication date: 12-Aug-2016
https://dl.acm.org/doi/10.1145/2979779.2979811
Russo BWagner SDi Penta M(2014)A proposed method to evaluate and compare fault predictions across studiesProceedings of the 10th International Conference on Predictive Models in Software Engineering10.1145/2639490.2639504(2-11)Online publication date: 17-Sep-2014
https://dl.acm.org/doi/10.1145/2639490.2639504
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Spam Filter Based Approach for Finding Fault-Prone Software Modules

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Published In

MSR '07: Proceedings of the Fourth International Workshop on Mining Software Repositories

May 2007

186 pages

ISBN:076952950X

Publisher

IEEE Computer Society

United States

Publication History

Published: 20 May 2007

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Cited By

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Halkidi MSpinellis DTsatsaronis GVazirgiannis M(2018)Data mining in software engineeringIntelligent Data Analysis10.5555/2010978.201098715:3(413-441)Online publication date: 27-Dec-2018
https://dl.acm.org/doi/10.5555/2010978.2010987
Kaur IBajpai N(2016)An Empirical Study on Fault Prediction using Token-Based ApproachProceedings of the International Conference on Advances in Information Communication Technology & Computing10.1145/2979779.2979811(1-7)Online publication date: 12-Aug-2016
https://dl.acm.org/doi/10.1145/2979779.2979811
Russo BWagner SDi Penta M(2014)A proposed method to evaluate and compare fault predictions across studiesProceedings of the 10th International Conference on Predictive Models in Software Engineering10.1145/2639490.2639504(2-11)Online publication date: 17-Sep-2014
https://dl.acm.org/doi/10.1145/2639490.2639504
Huang HXiao JYang QWang QWu H(2013)Creating Process-Agents incrementally by mining process asset libraryInformation Sciences: an International Journal10.1016/j.ins.2012.12.052233(183-199)Online publication date: 1-Jun-2013
https://dl.acm.org/doi/10.1016/j.ins.2012.12.052
Hattori Ldos Santos Jr GCardoso FSampaio Mda Silva Torres RRubira C(2008)Mining software repositories for software change impact analysisProceedings of the 23rd Brazilian symposium on Databases10.5555/1498932.1498953(210-223)Online publication date: 13-Oct-2008
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Hata HMizuno OKikuno THassan ALanza MGodfrey M(2008)An extension of fault-prone filtering using precise training and a dynamic thresholdProceedings of the 2008 international working conference on Mining software repositories10.1145/1370750.1370772(89-98)Online publication date: 10-May-2008
https://dl.acm.org/doi/10.1145/1370750.1370772
Mizuno OKikuno TCrnkovic IBertolino A(2007)Training on errors experiment to detect fault-prone software modules by spam filterProceedings of the the 6th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering10.1145/1287624.1287683(405-414)Online publication date: 7-Sep-2007
https://dl.acm.org/doi/10.1145/1287624.1287683

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