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SQA by Defect prediction: An SVM based In-Appendage Software Development Log Analysis

by N. Rajasekhar Reddy, R. J. Ramasree, R. MD. Shafi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 43 - Number 24
Year of Publication: 2012
Authors: N. Rajasekhar Reddy, R. J. Ramasree, R. MD. Shafi
10.5120/6437-8839

N. Rajasekhar Reddy, R. J. Ramasree, R. MD. Shafi . SQA by Defect prediction: An SVM based In-Appendage Software Development Log Analysis. International Journal of Computer Applications. 43, 24 ( April 2012), 15-22. DOI=10.5120/6437-8839

@article{ 10.5120/6437-8839,
author = { N. Rajasekhar Reddy, R. J. Ramasree, R. MD. Shafi },
title = { SQA by Defect prediction: An SVM based In-Appendage Software Development Log Analysis },
journal = { International Journal of Computer Applications },
issue_date = { April 2012 },
volume = { 43 },
number = { 24 },
month = { April },
year = { 2012 },
issn = { 0975-8887 },
pages = { 15-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume43/number24/6437-8839/ },
doi = { 10.5120/6437-8839 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:34:11.827221+05:30
%A N. Rajasekhar Reddy
%A R. J. Ramasree
%A R. MD. Shafi
%T SQA by Defect prediction: An SVM based In-Appendage Software Development Log Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 43
%N 24
%P 15-22
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The present paper proposes a Machine learning technique for defect forecasting and handling for SQA called appendage log training and analysis, can be referred as ALTA. The proposed defect forecasting of in-appendage software development logs works is to deal the forecasted defects accurately and spontaneously while developing the software. The present proposed mechanism helps in minimizing the difficulty of SQA. The overall study is conducted on evaluating the proposed model which indicates the defect forecasting in-appendage software development log training and analysis is significant growth to lessen the complexity of Software Quality Assessment.

References
  1. B. W. Boehm, J. R. Brown, H. Kaspar, M. Lipow, G. J. Macleod, and M. J. Merrit. Characteristics of Software Quality. North-Holland, 1978
  2. ISO. Software engineering – product quality – part 1: Quality model, 2001.
  3. D. Coleman, B. Lowther, and P. Oman. The application of software maintainability models in industrial software systems. J. Syst. Softw. , 29(1):3–16, 1995.
  4. M. R. Lyu, editor. Handbook of Software Reliability Engineering. IEEE Computer Society Press and McGraw-Hill, 1996.
  5. S. Wagner. Using economics as basis for modelling and evaluating software quality. In Proc. First International Workshop on the Economics of Software and Computation (ESC-1), 2007
  6. B. Kitchenham and S. L. Pfleeger. Software quality: The elusive target. IEEE Software, 13(1):12–21, 1996.
  7. E. Georgiadou. GEQUAMO—a generic, multilayered, cusomisable, software quality model. Software Quality Journal, 11:313–323, 2003.
  8. S. Khaddaj and G. Horgan. A proposed adaptable quality model for software quality assurance. Journal of Computer Sciences, 1(4):482–487, 2005.
  9. J. M¨unch and M. Kl¨as. Balancing upfront definition and customization of quality models. In Workshop-Band Software- Qualit¨atsmodellierung und -bewertung (SQMB 2008). Technische Universit¨at M¨unchen, 2008.
  10. M. Broy, F. Deissenboeck, and M. Pizka. Demystifying maintainability. In Proc. 4th Workshop on Software Quality (4-WoSQ), pages 21–26. ACM Press, 2006.
  11. F. Deißenb¨ock, S. Wagner, M. Pizka, S. Teuchert, and J. -F. Girard. An activity-based quality model for maintainability. In Proc. 23rd International Conference on Software Maintenance (ICSM '07). IEEE Computer Society Press, 2007.
  12. B. Kitchenham, S. Linkman, A. Pasquini, and V. Nanni. The SQUID approach to defining a quality model. Software Quality Journal, 6:211–233, 1997.
  13. V. Basili, P. Donzelli, and S. Asgari. A unified model of dependability: Capturing dependability in context. IEEE Software, 21(6):19–25, 2004.
  14. C. Frye. CMM founder: Focus on the product to improve quality, June 2008.
  15. N. Fenton. Software measurement: A necessary scientific basis. IEEE Trans. Softw. Eng. , 20(3):199–206, 1994.
  16. N. E. Fenton and M. Neil. A critique of software defect prediction models. IEEE Trans. Softw. Eng. , 25(5):675–689, 1999
  17. H. W. J. Rittel and M. M. Webber, "Dilemmas in a General Theory of Planning," Policy Sciences, vol. 4, no. 2, 1973, pp. 155–169.
  18. P. Abrahamsson et al. , "New Directions on Agile Methods: A Comparative Analysis," Proc. 25th Int'l Conf. Software Eng. (ICSE 03), IEEE CS Press, 2003, pp. 244–254.
  19. D. Saff and M. D. Ernst, "An Experimental Evaluation of Continuous Testing during Development," Proc. ACM SIGSOFT Int'l Symp. Software Testing and Analysis, ACM Press, 2004, pp. 76–85.
  20. D. C. Schmidt, "Guest Editor's Introduction: Model- Driven Engineering," Computer, vol. 39, no. 2, 2006, pp. 25–31.
  21. G. Karsai et al. , "Model-Integrated Development of Embedded Software," Proc. IEEE, vol. 91, no. 1, 2003, pp. 145–164.
  22. Cortes, C. ; Vapnik, V. ; Mach. Learn. 1995, 20, 273.
  23. Sun J, Xu W, Feng B, A Global Search Strategy of Quantum- Behaved Particle Swarm Optimization. In Proc. of the 2004 IEEE Conf. on Cybernetics and Intelligent Systems, Singapore: 291 – 294, 2004.
  24. Suykens, J. A. K. ; Vandewalle, J. ; Neural Process. Lett. 1999, 9, 293.
  25. Suykens, J. A. K. ; van Gestel, T. ; de Brabanter, J. ; de Moor, B. ; Vandewalle, J. ; Least-Squares Support Vector Machines, World Scientifics: Singapore, 2002.
  26. Zou, T. ; Dou, Y. ; Mi, H. ; Zou, J. ; Ren, Y. ; Anal. Biochem. 2006, 355, 1.
  27. Ke, Y. ; Yiyu, C. ; Chinese J. Anal. Chem. 2006, 34, 561.
  28. Niazi, A. ; Ghasemi, J. ; Yazdanipour, A. ; Spectrochim. Acta Part A 2007, 68, 523.
  29. Dr S. Nagaraja Rao, Dr. M. N. Giri Prasad "A New Image Compression framework :DWTOptimization using LS-SVM
  30. regression under IWP-QPSO
  31. based hyper parameter optimization", (IJCSIS) International Journal of Computer Science and Information Security,Vol. 9, No. 7, July 2011
  32. Florian Deissenboeck, Elmar Juergens, Klaus Lochmann, and Stefan Wagner "Software Quality Models: Purposes, Usage Scenarios and Requirements", Workshop on Software Quality 2009, Technische Universität München, Germany
Index Terms

Computer Science
Information Sciences

Keywords

Hybrid Software Development Method Conventional Software Development Methods Agile Software Development Methods Software Engineering

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