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Effective Bug Triage with Data Reduction

by S. R. Birajdar, H. B. Torvi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 10
Year of Publication: 2018
Authors: S. R. Birajdar, H. B. Torvi
10.5120/ijca2018917717

S. R. Birajdar, H. B. Torvi . Effective Bug Triage with Data Reduction. International Journal of Computer Applications. 182, 10 ( Aug 2018), 28-31. DOI=10.5120/ijca2018917717

@article{ 10.5120/ijca2018917717,
author = { S. R. Birajdar, H. B. Torvi },
title = { Effective Bug Triage with Data Reduction },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2018 },
volume = { 182 },
number = { 10 },
month = { Aug },
year = { 2018 },
issn = { 0975-8887 },
pages = { 28-31 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number10/29857-2018917717/ },
doi = { 10.5120/ijca2018917717 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:11:00.964932+05:30
%A S. R. Birajdar
%A H. B. Torvi
%T Effective Bug Triage with Data Reduction
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 10
%P 28-31
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

As human beings we all make mistakes and these mistakes are reflected as defects in the software product. These defects make the software fail which are due to our limitations as human beings. When the testing is done, the reasons for failure are identified and the defects are found. Then the defects are corrected. This is an iterative process- you need to test the software, fine defect, correct the code, and test software again. The defect has to be removed by developer. To remove defect which is not easy, Most of the organization spend 40% of cost to remove defect. The process of fixing or remove bug is bug triage. Remember every mistake in manual bug triggering, even those rated with the least priority. In order to reduce time, manual boom trials are applied to price, text classification techniques to take automated bug triage. In this paper, deal with the problem of data reduction for bug triage, i.e., how to reduce the scale and improve the quality of bug data. For the same combine instance selection and feature selection to reduce data scale on the bug dimension and the word dimension.

References
  1. W. Zou, Y. Hu, J. Xuan, and H. Jiang, “Towards training set reduction for bug triage,” in Proc. IEEE 35th Annual CS and Application Conference, Washington, DC, USA: IEEE Computer Society, 2011.
  2. Thomas Zimmermann, Rahul premraj, Jonathan Sillito, Silvia Brell, “Improving Bug Tracking Systems”, ICSE’09, May 2016.
  3. J. Anvik,”Automatic bug report assignment,” in Proc 28th International Conference on Software Engineering. ACM, 2006.
  4. H. Zhang, L. Gong, and S. Versteeg, “Predicting bug-fixing time: An empirical study of commercial software projects,” in Proc. 35th Int. Conf. Softw. Eng, May 2013.
  5. Shanthi Priya Duraisamy, Laxmi Raja, KalaiSelvi Kandaswamy,”An Approach for Predicting Bug Triage using Data Reduction Methods”in International Journal of Computer Applications ,November 2017
  6. Gaeul Jeong, Sunghun Kim,Thomas Zimmermann,” Improving Bug Triage with Bug Tossing Graphs”,in Proc. Joint Meeting 12th Eur. Softw.Eng.Conf.17th ACM SIGSOFT Symp. Found. Softw. Eng., Aug.2009.
  7. R. J. Sandusky, L. Gasser, and G. Ripoche, “Bug report networks: Varieties, strategies, and impacts in an F/OSS development community,” in Proc. 1st Intl. Workshop Mining Softw. Repositories, May 2004, pp. 80–84.
  8. T. Zimmermann, R. Premraj, N. Bettenburg, S. Just, A. Schr€oter, and C. Weiss, “What makes a good bug report?” IEEE Trans. Softw. Eng., vol. 36, no. 5, pp. 618–643, Oct. 2010.
  9. X. Wang, L. Zhang, T. Xie, J. Anvik, and J. Sun, “An approach to detecting duplicate bug reports using natural language and execution information,” in Proc. 30th Int. Conf. Softw. Eng., May 2008, pp. 461–470.
  10. C. Sun, D. Lo, S. C. Khoo, and J. Jiang, “Towards more accurate retrieval of duplicate bug reports,” in Proc. 26th IEEE/ACM Int Conf. Automated Softw. Eng., 2011, pp. 253–262.
  11. D. _Cubrani_c and G. C. Murphy, “Automatic bug triage using text categorization,” in Proc. 16th Int. Conf. Softw. Eng. Knowl. Eng., Jun. 2004, pp. 92–97.
  12. J. Anvik, L. Hiew, and G. C. Murphy, “Who should fix this bug?” in Proc. 28th Int. Conf. Softw. Eng., May 2006, pp. 361–370.
  13. J. Anvik and G. C. Murphy, “Reducing the effort of bug report triage: Recommenders for development-oriented decisions,” ACM Trans. Soft. Eng. Methodol., vol. 20, no. 3, article 10, Aug. 2011.
  14. Q. Hong, S. Kim, S. C. Cheung, and C. Bird, Understanding a developer social network and its evolution,” in Proc. 27th IEEE Int. Conf. Software Maintenance, Sep. 2011, pp. 323–332
  15. J. W. Park, M. W. Lee, J. Kim, S. W. Hwang, and S. Kim, “Costriage: A cost-aware triage algorithm for bug reporting systems,” in Proc. 25th Conf. Artif. Intell. Aug. 2011, pp. 139–144.
  16. Jifeng Xuan, He Jiang , Member ,IEEE, Yan Hu, Zhilei Ren, Weiqiu Zou, Zhongxuan Luo et al: Towards Effective Bug Triage with Data Reduction Techniques, in IEEE Transactions, vol.27, No.1 January 2015
  17. S.Shibaji E.J. Whitehead, Jr., R. Akella, and S. Kim, Reduction features to improve code changes based bug prediction, IEEE Trans. Soft. Eng., vol. 39, no. 4, pp.552-569, Apr.2013.
  18. Mamdouh Alenezi and Kenneth Magel: Efficient Bug Triaging Using Text Mining in 2013 Academy Publisher
Index Terms

Computer Science
Information Sciences

Keywords

Bug Triage Bug Report Instances Selection Feature Selection Data Reduction

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