Class level fault prediction using software clustering

2013 28th IEEE/ACM International Conference on Automated Software Engineering, ASE 2013 - Proceedings

Volumn , Issue , 2013, Pages 640-645

  Scanniello, Giuseppe ^a   Gravino, Carmine ^b   Marcus, Andrian ^c   Menzies, Tim ^d  

^a UNIVERSITY OF BASILICATA   (Italy)

^b UNIVERSITY OF SALERNO   (Italy)

^c WAYNE STATE UNIVERSITY   (United States)

^d WEST VIRGINIA UNIVERSITY   (United States)

Author keywords

Empirical Study; Fault Prediction; Software Clustering

Indexed keywords

EMPIRICAL INVESTIGATION; EMPIRICAL STUDIES; FAULT PREDICTION; FAULT PREDICTION MODELS; MULTIVARIATE LINEAR REGRESSIONS; OPEN SOURCE SOFTWARE SYSTEMS; SOFTWARE CLUSTERING; STRUCTURAL INFORMATION;

MATHEMATICAL MODELS;

COMPUTER SOFTWARE;

EID: 84893553028     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ASE.2013.6693126     Document Type: Conference Paper

References (35)

1. C. Catal and B. Diri, "Review: A systematic review of software fault prediction studies," Expert Syst. Appl., vol. 36, no. 4, pp. 7346-7354, 2009.
2. N. Nagappan, A. Zeller, T. Zimmermann, K. Herzig, and B. Murphy, "Change bursts as defect predictors," in Proc. of the International Symposium on Software Reliability Engineering. IEEE Computer Society, 2010, pp. 309-318.
3. N. Bettenburg, M. Nagappan, and A. E. Hassan, "Think locally, act globally: Improving defect and effort prediction models," in Proc. of the Working Conference o Mining Software Repositories. IEEE Computer Society, 2012, pp. 60-69.
4. T. Menzies, A. Butcher, D. Cok, A. Marcus, L. Layman, F. Shull, B. Turhan, and T. Zimmermann, "Local vs. global lessons for defect prediction and effort estimation," IEEE Trans. on Softw. Eng., no. PrePrints, p. 1, 2013.
5. T. Menzies, A. Butcher, A. Marcus, T. Zimmermann, and D. R. Cok, "Local vs. global models for effort estimation and defect prediction," in Proc. of the International Conference on Automated Software Engineering. IEEE Computer Society, 2011, pp. 343-351.
6. A. Schröter, T. Zimmermann, and A. Zeller, "Predicting component failures at design time," in Proc. of the International Symposium on Empirical Software Engineering. ACM, 2006, pp. 18-27. (Pubitemid 46634437)
7. T. Zimmermann, R. Premraj, and A. Zeller, "Predicting defects for eclipse," in Proc. of the International Workshop on Predictor Models in Software Engineering. IEEE Computer Society, 2007, pp. 9-.
8. Z. Li, L. Tan, X. Wang, S. Lu, Y. Zhou, and C. Zhai, "Have things changed now?: an empirical study of bug characteristics in modern open source software," in Proc. of the Workshop on Architectural and System Support for Improving Software Dependability. ACM, 2006, pp. 25-33. (Pubitemid 47113410)
9. T. Menzies, B. Caglayan, E. Kocaguneli, J. Krall, F. Peters, and B. Turhan, "The PROMISE Repository of empirical software engineering data," 2012. [Online]. Available: http://promisedata.googlecode.com
10. E. Arisholm, L. C. Briand, and E. B. Johannessen, "A systematic and comprehensive investigation of methods to build and evaluate fault prediction models," J. Syst. Softw., vol. 83, no. 1, pp. 2-17, 2010.
11. N. Nagappan, T. Ball, and A. Zeller, "Mining metrics to predict component failures," in Proc. of the International Conference on Software Engineering. ACM, 2006, pp. 452-461. (Pubitemid 46600942)
12. Y. Kamei, S. Matsumoto, A. Monden, K.-i. Matsumoto, B. Adams, and A. E. Hassan, "Revisiting common bug prediction findings using effortaware models," in Proc. of the International Conference on Software Maintenance. IEEE Computer Society, 2010, pp. 1-10.
13. X. Tan, X. Peng, S. Pan, and W. Zhao, "Assessing software quality by program clustering and defect prediction," in Proc. of the Working Conference on Reverse Engineering. IEEE Computer Society, 2011, pp. 244-248.
14. J. Buckner, J. Buchta, M. Petrenko, and V. Rajlich, "JRipples: A tool for program comprehension during incremental change," in Proc. of the International Workshop on Program Comprehension. IEEE Computer Society, 2005, pp. 149-152. (Pubitemid 41624372)
15. A. C. N. Ngomo, "Low-bias extraction of domain-specific concepts," Ph.D Thesis, 2009.
16. G. Scanniello and A. Marcus, "Clustering support for static concept location in source code," in Proc. of the International Conference on Program Comprehension. IEEE Computer Society, 2011, pp. 1-10.
17. V. R. Basili, L. C. Briand, and W. L. Melo, "A validation of objectoriented design metrics as quality indicators," IEEE Trans. Softw. Eng., vol. 22, no. 10, pp. 751-761, 1996. (Pubitemid 126771690)
18. T. Gyimóthy, R. Ferenc, and I. Siket, "Empirical validation of objectoriented metrics on open source software for fault prediction," IEEE Trans. Software Eng., vol. 31, no. 10, pp. 897-910, 2005. (Pubitemid 43065752)
19. Y. Zhou and H. Leung, "Empirical analysis of object-oriented design metrics for predicting high and low severity faults," IEEE Trans. on Softw. Eng., vol. 32, no. 10, pp. 771-789, 2006. (Pubitemid 46405591)
20. V. Basili, G. Caldiera, and D. H. Rombach, The Goal Question Metric Paradigm, Encyclopedia of Software Engineering. John Wiley and Sons, 1994.
21. S. R. Chidamber and C. F. Kemerer, "A metrics suite for object oriented design," IEEE Trans. Softw. Eng., vol. 20, no. 6, pp. 476-493, 1994.
22. S. Di Martino, F. Ferrucci, C. Gravino, and F. Sarro, "A genetic algorithm to configure support vector machines for predicting fault-prone components," in Proc. of International Conference on Product-focused Software Process Improvement. Springer-Verlag, 2011, pp. 247-261.
23. B. A. Kitchenham, E. Mendes, and G. H. Travassos, "Cross versus within-company cost estimation studies: A systematic review," IEEE Transactions on Software Engineering, vol. 33, no. 5, pp. 316-329, 2007. (Pubitemid 46681200)
24. T. Hall, S. Beecham, D. Bowes, D. Gray, and S. Counsell, "A systematic literature review on fault prediction performance in software engineering," IEEE Trans. on Softw. Eng., vol. 38, no. 6, pp. 1276-1304, 2012.
25. T. J. Hastie and D. Pregibon, Generalized linear models, J. M. Chambers and T. J. Hastie, Eds. Wadsworth and Brooks/Cole, 1992.
26. S. Geisser, Predictive Inference: An Introduction, ser. Chapman and Hall/CRC Monographs on Statistics and Applied Probability Series. Chapman and Hall, 1993.
27. L. C. Briand and J. Wüst, "Modeling development effort in objectoriented systems using design properties," IEEE Trans. Softw. Eng., vol. 27, no. 11, pp. 963-986, 2001. (Pubitemid 33106026)
28. E. Kocaguneli, T. Menzies, and J. W. Keung, "Kernel methods for software effort estimation - effects of different kernel functions and bandwidths on estimation accuracy," Empirical Software Engineering, vol. 18, no. 1, pp. 1-24, 2013.
29. E. Kocaguneli, T. Zimmermann, C. Bird, N. Nagappan, and T. Menzies, "Distributed development considered harmful?" in Proc. of the International Conference on Software Engineering. IEEE Computer Society, 2013, pp. 882-890.
30. W. J. Conover, Practical Nonparametric Statistics. Wiley, 3rd Edition, 1998.
31. Wohlin, C., Runeson, P., Höst, M., Ohlsson, M.C., Regnell, B., and Wesslén, A., Experimentation in Software Engineering - An Introduction. Kluwer Academic Publishers, 2000.
32. V. Kampenes, T. Dyba, J. Hannay, and I. Sjoberg, "A systematic review of effect size in software engineering experiments," Information and Software Technology, vol. 49, no. 11-12, pp. 1073-1086, 2006.
33. J. B. Kevin Freedman, "Current concepts review - sample size and statistical power in clinical orthopaedic research," Journal of Bone & Joint Surgery, vol. 81, pp. 1454-60, 1999.
34. S. Shapiro and M. Wilk, "An analysis of variance test for normality," Biometrika, vol. 52, no. 3-4, pp. 591-611, 1965.
35. B. Kitchenham, H. Al-Khilidar, M. Babar, M. Berry, K. Cox, J. Keung, F. Kurniawati, M. Staples, H. Zhang, and L. Zhu, "Evaluating guidelines for reporting empirical software engineering studies," Empirical Software Engineering, vol. 13, pp. 97-121, 2008.