International Journal of Modern Education and Computer Science (IJMECS)
IJMECS Vol. 7, No. 9, 8 Sep. 2015
Cover page and Table of Contents: PDF (size: 436KB)
An Insight to Soft Computing based Defect Prediction Techniques in Software
Full Text (PDF, 436KB), PP.52-58
Views: 0 Downloads: 0
Author(s)
Index Terms
Software Defects, Software Defect Prediction, Software Defect Prediction Models, Soft Computing techniques, machine Learning Techniques
Abstract
Nowadays, the complexity and size of software systems is proliferating. These factors have various pros and cons. On one side where they lead to better performance and satisfactory results, on the other side they lead to high testing cost , wacky results , poor quality and non-reliability of the product. These problems have one root cause which is referred to as defects in the software systems Predicting these defects can not only rule out the cons but can also boost up the pros. Various techniques are present for the same which are reviewed in depth in this paper. Moreover, a comparison of these techniques is also done to throw a lime light on those which provide the best results.
Cite This Paper
Kritika Verma, Pradeep Kumar Singh, "An Insight to Soft Computing based Defect Prediction Techniques in Software", IJMECS, vol.7, no.9, pp.52-58, 2015. DOI:10.5815/ijmecs.2015.09.07
Reference
[1]K. Punitha, Dr. S. Chitra, “Software Defect Prediction Using Software Metrics-A Survey,” IEEE International Conference on Information Communication and Embedded Systems, pp. 555-558, 2013.
[2]Y.Xia, G.Yan, Q.Si, “A Study on the Significance Of Software Metrics In Defect Prediction,” IEEE Sixth International Symposium On Computational Intelligence And Design, pp. 343-346, 2013.
[3]H.Wang, T.M.Khoshgoftaar, N.Seliya, “How Many Software Metrics Should Be Selected For Defect Prediction,” In Proceedings Of Twenty-Fourth International Florida Artificial Intelligence Research Society Conference, pp. 69-74, 2011.
[4]H.A.Al-Jamimi, L.Ghouti, “Efficient Prediction Of Software Fault Proneness Modules Using Support Vector Machines And Probabilistic Neural Network,” IEEE Fifth Malaysian Conference In Software Engineering, pp. 251-256, 2011.
[5]K.Sankar, S.Kannan, P.Jennifer, “Prediction Of Code Fault Using Naïve Bayes And Svm Classifiers,” Middle-East Journal Of Scientific Research, Vol. 20, No. 1, pp. 108-113, 2014.
[6]R.S.Wahono, N.S.Herman, S.Ahmad, “A Comparison Framework Of Classification Models For Software Defect Prediction,” American Scientific Publishers , Vol. 20 , No. 10-11 , pp. 1945-1950, 2014.
[7]Er.R.Mahajan, Dr.S.K.gupta , R.K.Bedi, “Comparison Of Various Approaches Of Software Fault Prediction: A Review,” International Journal Of Advanced Technology & Engineering Research , Vol. 4 , No. 4, pp. 13-16, 2014.
[8]P.Paramshetti, D.A.Phalke, “Survey On Software Defect Prediction Using Machine Learning Techniques,” International Journal Of Science And Research, Vol. 3, No. 12, pp. 1394-1397, 2014.
[9]A.A.S.Haghighi, M.A.Dezfuli , S.M.Fakhra, “Applying Mining Schemes To Software Fault Prediction: A Proposed Approach Aimed At Test Cost Reduction,’ Proceedings Of The World Congress On Engineering, Vol. 1, p. 415, 2014.
[10]L.Sehgal, N.Mohan, Dr.P.S.Sandhu, “Quality Prediction Of Function Based Software Using Decision Tree Approach,” International Conference On Computer Engineering And Multimedia Technologies, pp. 43-47, 2012.
[11]N.Gayathri, S.Nikolas, A.V.Reddy, “Feature Selection Using Decision Tree Induction in Class Level Metrics Dataset for Software Defect Predictions,” In Proceedings of the World Congress on Engineering and Computer Science, Vol. 1, 2010.
[12]R.Jindal, R.Malhotra, A.Jain, “Software Defect Prediction Using Neural Networks,” IEEE Third International Conference On Reliability, Infocom Technologies And Optimization, pp. 1-6, 2014.
[13]M.Gayathri, A.Sudha, “Software Defect Prediction System Using Multilayer Perceptron Neural Network With Data Mining,” International Journal Of Recent Technology And Engineering, Vol. 3, No. 2, pp 54-59, 2014.
[14]M.M.T.Thwin, T.S.Quah, “Application Of Neural Network For Predicting Software Development Faults Using Object Oriented Design Metrics,” In Proceedings Of The Ninth International Conference On Neural Information Processing, p. 2312-2316, 2002.
[15]N.E.Fenton, M.Neil, “A Critique of Software Defect Prediction Models,” IEEE Transactions on Software Engineering, Vol. 25, No. 5, pp. 675-689, 1999.
[16]W.Tao, L.Wei-Hua, “Naïve Bayes Software Defect Prediction Model,” International Conference on Computational Intelligence and Software Engineering, pp. 1-4, 2010.
[17]Y.Liu, W.P.Cheah, B.K.Kim, H.Park, “Predict Software Failure-Prone By Learning Bayesian Network,” International Journal of Advanced Science and Technology, Vol. 33, No. 10, pp 35-42, 2008.
[18]G.D.Boetticher, “Nearest Neighbour Sampling for Better Defect Prediction,” ACM Journal, Vol. 30, No. 4, pp.1-6, 2005.
[19]T.Zimmermann, R.Premraj, A.Zeller, “Predicting Defects For Eclipse,” International Workshop On Predictor Models In Software Engineering, 2007.
[20]P.A.Selvaraj, Dr.P.Thangaraj, “Support Vector Machine for Software Defect Prediction,” International Journal of Engineering & Technology Research, Vol. 1, Issue 2, pp. 68-76, 2013.
[21]Y.Singh, A.Kaur, R.Malhotra, “Software Fault Proneness Prediction Using Support Vector Machines,” In Proceedings of the World Congress on Engineering, Vol. 1, 2009.
[22]Y.Weimen, L.Longshu, “A Rough Set Model for Software Defect Prediction,” International Conference on Intelligent Computation Technology & Automation, pp. 747-751, 2008.
[23]M.Liu, L.Miao, D.Zhang, “Two Stage Cost Sensitive Learning For Software Defect Prediction,” IEEE Transactions on Reliability, Vol. 63, No, 2, pp. 676-686, 2014.
[24]M.D.Ambros, M.Lanza, R.Robbes, “An Extensive Comparison of Bug Prediction Approaches,” IEEE Seventh International Conference on Mining Software Repositories, pp. 31-41, 2010.
[25]R.Malhotra, “Comparative Analysis Of Statistical And Machine Learning Methods For Predicting Faulty Modules,” Elsevier Journal Of Applied Soft Computing, Vol. 21, pp. 286-297, 2014.
[26]www.softwaretestingclass.com/top-10-0reasons-why-there-are-defects-in-software/last accessed on 7/03/2015.
[27]Gunjan Goswami, Data Mining and Data Warehouse, Katsons Publishers, New Delhi, Chapter 5, Chapter 6, Chapter 7, 2012.
[28]S.N.Sivanandam and S.N.Deepa (2013). Principles Of Soft Computing, Wiley Publishers, Coimbatore, Chapter 3, Chapter 5, Chapter 6, Chapter 7, 2013.
[29]Pradeep Kumar Singh, O.P. Sangwan and A. Sharma (2013). A Systematic Review on Fault Based Mutation Testing Techniques and Tools for Aspect-J Programs, published in 3rd IEEE International Advance Computing Conference, IACC-2013 at AKGEC Ghaziabad, India, 22-23, February 2013, IEEE Xplore, pp. 1455-1461.