Fault prediction modeling for software quality estimation: Comparing commonly used techniques

Empirical Software Engineering

Volumn 8, Issue 3, 2003, Pages 255-283

  Khoshgoftaar, Taghi M ^a   Seliya, Naeem ^a  

^a FLORIDA ATLANTIC UNIVERSITY   (United States)

Author keywords

CART; Case based reasoning; Fault prediction; Multiple linear regression; Neural networks; S PLUS; Software metrics; Software quality prediction

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; KNOWLEDGE BASED SYSTEMS; NEURAL NETWORKS; PRINCIPAL COMPONENT ANALYSIS; REGRESSION ANALYSIS; RELIABILITY; TELECOMMUNICATION SYSTEMS;

CASE-BASED REASONING; FAULT PREDICTION MODELING; MULTIPLE LINEAR REGRESSION; SOFTWARE METRICS; SOFTWARE QUALITY PREDICTION;

COMPUTER SOFTWARE SELECTION AND EVALUATION;

EID: 0042767590     PISSN: 13823256     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1024424811345     Document Type: Article

References (37)

1. Beaumont, G. P. 1996. Statistical Tests: An Introduction with Minitab Commentary. Prentice Hall.
2. Berenson, M. L., Levine, D. M., and Goldstein, M. 1983. Intermediate Statistical Methods and Applications: A Computer Package Approach. Englewood Cliffs, NJ, USA: Prentice Hall.
3. Breiman, L., Friedman, J. H., Olshen, R. A., and Stone, C. J. 1984. Classification And Regression Trees. Belmont, California, USA: Wadsworth International Group, 2nd edition.
4. Briand, L. C., Basili, V. R., and Hetmanski, C. J. 1993. Developing interpretable models with optimized set reduction for identifying high-risk software components. IEEE Transactions on Software Engineering 19(11): 1028-1044.
5. Briand, L. C., Langley, T., and Wiezorek, I. 2000. A replicated assessment and comparison of common software cost modeling techniques. In Proceedings: International Conference on Software Engineering. Limerick, Ireland, 377-386.
6. Clark, L. A., and Pregibon, D. 1992. Tree-based models. In J. M. Chambers and T. J. Hastie (eds.): Statistical Models in S. Pacific Grove, California: Wadsworth International Group, pp. 377-419.
7. Fenton, N. E., and Pfleeger, S. L. 1997. Software Metrics: A Rigorous and Practical Approach, second edition, Boston, MA, USA: PWS Publishing Company: ITP.
8. Finnie, G. R., Wittig, G. E., and Desharnais, J. M. 1997. A comparison of software effort estimation techniques: using function points with neural networks, case-based reasoning, and regression models. Journal of Systems and Software 39: 281-289.
9. Ganesan, K., Khoshgoftaar, T. M., and Allen, E. B. 2000. Case-based software quality prediction. International Journal of Software Engineering and Knowledge Engineering 10(2): 139-152. World Scientific Publishing.
10. Gokhale, S. S., and Lyu, M. R. 1997. Regression tree modeling for the prediction of software quality. In H. Pham (ed.): Proceedings: 3rd International Conference on Reliability and Quality in Design. Anaheim, California, USA, 31-36.
11. Gray, A. R., and MacDonell, S. G. 1999. Software metrics data analysis: exploring the relative performance of some commonly used modeling techniques. Empirical Software Engineering 4: 297-316.
12. Hudepohl, J. P., Aud, S. J., Khoshgoftaar, T. M., Allen, E. B., and Mayrand, J. 1996. Emerald: Software metrics and models on the desktop. IEEE Software 13(5): 56-60.
13. Jones, W. D., Hudepohl, J. P., Khoshgoftaar, T. M., and Allen, E. B. 1999. Application of a usage profile in software quality models. In Proceedings: 3rd European Conference on Software Maintenance and Reengineering. Amsterdam, Netherlands, 148-157.
14. Khoshgoftaar, T. M., and Allen, E. B. 2001. Modeling software quality with classification trees. In H. Pham (ed.): Recent Advances in Reliability and Quality Engineering. Singapore: World Scientific Publishing, Chapter 15, 247-270.
15. Khoshgoftaar, T. M., Allen, E. B., and Busboom, J. C. 2000a. Modeling software quality: the software measurement analysis and reliability toolkit. In Proceedings: 12th International Conference on Tools with Artificial Intelligence. Vancouver, BC Canada, 54-61.
16. Khoshgoftaar, T. M., Allen, E. B., and Deng, J. 2001. Controlling overfitting in software quality models: experiments with regression trees and classification. In Proceedings: 7th International Software Metrics Symposium. London UK, 190-198.
17. Khoshgoftaar, T. M., Allen, E. B., Jones, W. D., and Hudepohl, J. P. 2000b. Accuracy of software quality models over multiple releases. Annals of Software Engineering 9(1-4): 103-116.
18. Khoshgoftaar, T. M., Allen, E. B., and Shan, R. 2000c. Improving tree-based models of software quality with principal components analysis. In Proceedings of the Eleventh International Symposium on Software Reliability Engineering. San Jose, California, USA, 198-209.
19. Khoshgoftaar, T. M., and Lanning, D. L. 1995. A neural network approach for early detection of pro-gram modules having high risk in the maintenance phase. Journal of Systems and Software 29(1): 85-91.
20. Khoshgoftaar, T. M., Munson, J. C., Bhattacharya, B. B., and Richardson, G. D., 1992. Predictive modeling techniques of software quality from software measures. IEEE Transactions on Software Engineering 18(11): 979-987.
21. Khoshgoftaar, T. M., and Seliya, N. 2002. Tree-based software quality models for fault prediction. In Proceedings: 8th International Software Metrics Symposium. Ottawa, Ontario, Canada, 203-214.
22. Kolodner, J. 1993. Case-Based Reasoning. San Mateo, California, USA: Morgan Kaufmann Publishers, Inc.
23. Lin, C. T., and Lee, C. S. G. 1996. Neural Fuzzy Systems: A Neuro-Fuzzy Synergism to Intelligent Systems. Upper Saddle River, NJ, USA: Prentice Hall Inc.
24. Lippmann, R. P. 1987. An introduction to computing with neural networks. Acoustics, Speech and Signal Processing Magazine 4(2): 4-22.
25. Minsky, M., and Papert, S. 1969. Perceptrons. MA, USA: MIT Press.
26. Neter, J., Kutner, M. H., Nachtsheim, C. J., and Wasserman, W. 1996. Applied Linear Statistical Models. Tom Casson.
27. Nielsen, R. H. 1987. Counter propagation network. Applied Optics Journal 26(23).
28. Ohlsson, M. C., and Runseon, P. 2002. Experience from replicating empirical studies on prediction models. In Proceedings: 8th International Software Metrics Symposium. Ottawa, Ontario, Canada, 217-226.
29. Rosenblatt, F. 1962. Principles of Neurodynamics: Perceptrons and the Theory of Brain Mechanisms. New York, NY, USA: Spartan Books.
30. Rumelhart, D. E., Hinton, G. E., and Williams, R. 1962. Parallel Distributed Processing, Vol. 1. Cambridge, MA, USA: MIT Press.
31. Schneidewind, N. F. 1995. Software metrics validation: space shuttle flight software example. Annals of Software Engineering 1: 287-309.
32. Schneidewind, N. F. 1997. Software metrics model for integrating quality control and prediction. In Proceedings: 8th International Symposium on Software Reliability Engineering. Albuquerque, NM USA, 402-415.
33. Seliya, N. 2001. Software fault prediction using tree-based models. Master's thesis, Florida Atlantic University, Boca Raton, FL USA. Advised by T. M. Khoshgoftaar.
34. Sundaresh, N. 2001. An empirical study of analogy based software fault prediction. Master's thesis, Florida Atlantic University, Boca Raton, FL USA. Advised by Taghi M. Khoshgoftaar.
35. Takahashi, R., Muraoka, Y., and Nakamura, Y. 1997. Building software quality classification trees: approach, experimentation, evaluation. In Proceedings: 8th International Symposium on Software Reliability Engineering. Albuquerque, NM, USA, 222-233.
36. Troster, J., and J. Tian 1995. Measurement and defect modeling for a legacy software system. Annals of Software Engineering 1: 95-118.
37. Xu, Z. 2001. Fuzzy logic techniques for software reliability engineering. Ph.D. thesis, Florida Atlantic University, Boca Raton, Florida USA. Advised by Taghi M. Khoshgoftaar.