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Software Bug Detection using Data Mining

by Dhyan Chandra Yadav, Saurabh Pal
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 115 - Number 15
Year of Publication: 2015
Authors: Dhyan Chandra Yadav, Saurabh Pal
10.5120/20228-2513

Dhyan Chandra Yadav, Saurabh Pal . Software Bug Detection using Data Mining. International Journal of Computer Applications. 115, 15 ( April 2015), 21-25. DOI=10.5120/20228-2513

@article{ 10.5120/20228-2513,
author = { Dhyan Chandra Yadav, Saurabh Pal },
title = { Software Bug Detection using Data Mining },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 115 },
number = { 15 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 21-25 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume115/number15/20228-2513/ },
doi = { 10.5120/20228-2513 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:54:55.359809+05:30
%A Dhyan Chandra Yadav
%A Saurabh Pal
%T Software Bug Detection using Data Mining
%J International Journal of Computer Applications
%@ 0975-8887
%V 115
%N 15
%P 21-25
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The common software problems appear in a wide variety of applications and environments. Some software related problems arises in software project development i. e. software related problems are known as software defect in which Software bug is a major problem arises in the coding implementation . There are no satisfied result found by project development team. The software bug problems mentation in problem report and software engineer does not easily detect this software defect but by the help of data mining classification software engineers easily can classify software bug. This paper classified and detect software bug by J48, ID3 and Naïve Bayes data mining algorithms. Comparison of these algorithms to detect accuracy and time taken to build model is also presented in this paper.

References
  1. Hampherey Watts S. , "A discipline for software Engineering reading", Ma,Addison Wesley,1995.
  2. Sunita Tiwari and Neha Chaudhary, "Data mining and Warehousing" Dhanpati Rai and Co. (P) Ltd. First Edition: 2010.
  3. J. R. Quinlan, "C4. 5: programs for machine learning", Morgan Kaufmann,San Francisco,1993.
  4. M. Shepperd, C. Schofield, and B. Kitchenham, "Effort estimation using analogy," in of the 18th International Conference On Software Engineering, pp. 170- 178. Berlin, Germany, 1996.
  5. Alsmadi and Magel, "Open source evolution Analysis," in proceeding of the 22nd IEEE International Conference on Software Maintenance (ICMS'06), phladelphia, pa. USA, 2006.
  6. Boehm, Clark, Horowitz, Madachy, Shelby and Westland, "Cost models for future software life cycle Process: COCOMO2. 0. " in Annals of software Engineering special volume on software process and prodocuct measurement, J. D. Arther and S. M. Henry, Eds, vol. 1, pp. 45-60, j. c. Baltzer AG, science publishers, Amsterdam ,The Netherlands, 1995.
  7. Pal A. K. , and Pal S. , "Analysis and Mining of Educational Data for Predicting the Performance of Students", (IJECCE) International Journal of Electronics Communication and Computer Engineering, Vol. 4, Issue 5, pp. 1560-1565, ISSN: 2278-4209, 2013.
  8. Ribu, Estimating, "Object oriented software projects With use cases", M. S. thesis, University of Oslo Department of informatics, 2001.
  9. Nagwani N. and Verma S. , "Prediction data mining Model for software bug estimation using average Weighted similiarity," In proceeding of advance Computing conference (IACC), 2010.
  10. Hassan, "The road ahead for mining software Repositories", in processing of the future of software Maintenance at the 24th IEEE international Conference on software maintenance, 2008.
  11. Chauraisa V. and Pal S. , "Data Mining Approach to Detect Heart Diseases", International Journal of Advanced Computer Science and Information Technology (IJACSIT),Vol. 2, No. 4,2013, pp 56-66.
  12. Chauraisa V. and Pal S. , "Early Prediction of Heart Diseases Using Data Mining Techniques", Carib. j. SciTech,,Vol. 1, pp. 208-217, 2013.
  13. Li and Reformat, "A practical method for the Software fault prediction", in proceeding of IEEE Nation conference information reuse and Integration (IRI), 2007.
  14. Elcan C. , "The foundations of cost sensitive learning", In processing of the 17 International conference on Machine learning, 2001.
  15. Chang and Chu, "software defect prediction Using international association rule mining", 2009.
  16. Kotsiantis and Kanellopoulos, "Associationn rule mining: A recent overview", GESTS international transaction on computer science and Engineering, 2006.
  17. Pannurat, Kerdprasop and Kerdprasop, "Database reverses engineering based On Association rule mining", IJCSI international Journal Of computer science issues 2010.
  18. Fayyad, Piatesky Shapiro, Smuth and Uthurusamy, "Advances in knowledge discovery And data mining", AAAI Press,1996.
  19. Pal S. , "Mining Educational Data to Reduce Dropout Rates of Engineering Students", I. J. Information Engineering and Electronic Business (IJIEEB), Vol. 4, No. 2, 2012, pp. 1-7.
  20. Shtern and Vassilios, "Review article advances in Software engineering clustering methodologies for software engineering", Tzerpos volume, 2012.
  21. Runeson and Nyholm, "Detection of duplicate Defect report uses neural network processing", in Proceeding of the 29th international conference on Software engineering 2007.
  22. Vishal and Gurpreet, "A survey of text mining Techniques and applications", journal of engineering Technologies in web intelligence, 2009.
  23. Lovedeep and Varinder Kaur Arti, "Application of Data mining techniques in software engineering" International journal of electrical, electronics and computer system(IJEECS) Volume-2 issue-5, 6. 2014.
  24. Yadav S. K. and Pal S. , "Data Mining: A Prediction for Performance Improvement of Engineering Students using Classification", World of Computer Science and Information Technology (WCSIT), 2(2), 51-56, 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Classification: ID3 J48 and Naïve Bayes Software BUG WEKA.

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