AN EMPIRICAL ANALYSIS OF METRICS TO PREDICT THE SOFTWARE DEFECT FIX-EFFORT

Bindu Goel and Yogesh Singh

References

  1. [1] J. Feller & B. Fitzgerald, A framework analysis of the opensource software development paradigm, Proceedings of theTwenty First International Conference on Information Sys-tems, Australia, 2000, 58–69.
  2. [2] P. Bourque, S. Olingy, A. Abran, & B. Fournier, Developingproject duration models in software engineering, Journal ofComputer Science and Technology, 22(3), 2007, 348–357.
  3. [3] B. Boehm, B. Clark, E. Horowitz, C. Westland, R. Madachy,& R. Selby, Cost models for future software life cycle pro-cesses: COCOMO 2.0. USC Center for Software Engineering,1995, http://sunset.usc.edu/publications/TECHRPTS/1995/index.html.
  4. [4] K. Manzoor, A practical approach to estimate defect-fix time,http://homepages.com.pk/kashman/defectsEstimation.htm.
  5. [5] M. Alshayeb & W. Li, An empirical validation of object-oriented metrics in two different iterative software processes,IEEE Transactions on Software Engineering, 29(11), 2003,1043–1049.
  6. [6] Y. Singh & B. Goel, Empirical investigation of metrics for faultprediction on object-oriented software, Published as a chapterin “Studies in Computational Intelligence by Springer Berlin/Heidelberg Germany (ICIS 2008), 255–265.
  7. [7] G. Denaro & M. Pezze, An empirical evaluation of pronenessmodels, Proceedings of International Conference on SoftwareTesting, ICSE 2002, Buneos Aires, Argentina, 2002.130
  8. [8] W.M. Evanco, Prediction models for software fault correc-tion, Proceedings of the Fifth European Conference on Soft-ware Maintenance and Reengineering (CSMR’01), IEEE, USA,2001, 114–120.
  9. [9] Y. Singh & B. Goel, An integrated model to predict faultproneness using neural networks, Journal Software QualityProfessional, ASQ, 10(2), 2008, 22–32.
  10. [10] F. Fioravanti, A metric framework for the assessment of object-oriented systems, Ph.D. Thesis, Dip. Sistemi e Informatica,1999, www.fioravanti.firenze.it/id22.htm.
  11. [11] W. Li & S. Henry, Object-oriented metrics that predict main-tainability, Journal of Systems and Software, 23(2), 1993,111–122.
  12. [12] F. Fioravanti & P. Nesi, Estimation and prediction metricsfor adaptive maintenance effort of object-oriented systems,IEEE Transactions on Software Engineering, 27(12), 2001,1062–1084.
  13. [13] V. Basili, L. Briand, S. Condon, Y. Kim, W. Melo, & J.Valett, Understanding and predicting the process of softwaremaintenance releases, Proc. Eighth Intl Conf. on SoftwareEngineering (ICSE-18), Berlin, Germany, 1996.
  14. [14] P. Nesi & T. Querci, Effort estimation and prediction of object-oriented systems, Journal of Systems and Software, 42(1),1998, 89–102.
  15. [15] A. Mockus, D. Weiss, & P. Zhang, Understanding and predict-ing effort in software projects, 25th International Conferenceon Software Engineering, Portland, Oregon, 3–10 May, 2003,274–284.
  16. [16] B. Goel & Y. Singh, An empirical analysis of metrics topredict the maintainability for real-time object-oriented soft-ware, Journal Software Quality Professional, ASQ, 11(3), 2009,35–45.
  17. [17] H. Zeng & D. Rine, Estimation of software defects fix-effortusing neural networks, Proceedings of the 28th Annual In-ternational Computer Software and Applications Conference(COMPSAC’04), Los Alamitos, 28–30 September, 2004, 2,20–21.
  18. [18] A. Mockus, D.M. Weiss, & P. Zhang, Understanding andpredicting effort in software projects, IEEE 2003.
  19. [19] H.S. Chae, T.Y. Kim, W.-S. Jung, & J.-S. Lee, Using metrics forestimating maintainability of web applications: An empiricalstudy, 6th IEEE/ACIS International Conference on Computerand Information Science, Melbourne, Australia, ICIS 2007.
  20. [20] Y. Singh & B. Goel, Empirical assessment of LR and ANNbased software fault prediction techniques, European Comput-ing Conference, Athens, Greece, 2007.
  21. [21] S. Bibi, G. Tsoumakas, I. Stamelos, & I. Vlahavas, Regressionvia classification applied on software defect estimation, ExpertSystems with Applications, 34 (3), 2007, 2091–2101.
  22. [22] N. Fenton & S. Pfleeger, Software metrics. A rigorous andpractical approach, Second Edition (Boston, MA: ThomsonComputer Press, 1997).
  23. [23] S.R. Chidamber & C.F. Kemerer, A metrics suite for objectoriented design, IEEE Transactions on Software Engineering,20(6), 1994, 476–493.
  24. [24] T. McCabe, A complexity measure, IEEE Transactions onSoftware Engineering, 2(4), 1976, 308–320.
  25. [25] S. Henry & D. Kafura, Software structure metrics based oninformation flow, IEEE Transactions on Software Engineering,7(5), 1981, 510–518.
  26. [26] W. Dillon & M. Goldstein, Multivariate analysis: Methods andApplications (New York: John Wiley & Sons, 1984).
  27. [27] L.C. Briand & I. Wieczorek, Software resource estimation,Encyclopedia of Software engineering, P-Z(2), 2002, 1160–1196.
  28. [28] D. Belsley, E. Kuh, & R. Welsch, Regression diagnostics:Identifying influential data and sources of collinearity (NewYork: John Wiley and Sons, 1980).
  29. [29] R.D. Cook & S. Weisberg, Residual and influence in regression(London: Chapman and Hall, 1982).
  30. [30] I. Myrtveit, E. Stensrud, & M. Shepperd, Reliability andvalidity in comparative studies of software prediction models,IEEE Transactions on Software Engineering, 31(5), 2005,380–391.
  31. [31] C.F. Kemerer, An empirical validation of software cost esti-mation models, CACM, 30(5), 1987, 416–429.
  32. [32] M.J. Shepperd, C. Schofield, & B. Kitchenham, Effort estima-tion using analogy, Proc. ICSE-18, Berlin, 1996.
  33. [33] I. Myrtveit & E. Stensrud, A controlled experiment to assessthe benefits of estimating with analogy and regression models,IEEE Transactions on Software Engineering, 25(4), 1999,510–525.
  34. [34] B. Efron & G. Gong, A leisurely look at the bootstrap, thejackknife, and cross-validation, The American Statistician,37(1), 1983, 36–48.
  35. [35] M.R. Lyu, Handbook of software reliability engineering (LosAlamitos, California, USA: McGraw Hill, 1996).
  36. [36] L. Briand, T. Langley, & I. Wieczorek, A replicated assess-ment and comparison of common software cost modeling tech-niques, Proc. of 22nd International Conference on SoftwareEngineering, Limerick, Ireland, 2000, 377–386.
  37. [37] R. Jeffery, M. Ruhe, & I. Wieczorek, A comparative studyof two software development cost modeling techniques usingmulti-organizational and company-specific data, Informationand Software Technology, 42(14), 2000, 1009–1016.
  38. [38] A. De Lucia, E. Pompella, & S. Stefanucci, Assessing effort pre-diction models for corrective, software maintenance enterprise(Netherlands: Springer, 2006), 55–62.
  39. [39] S. Conte, H. Dunsmore, & V. Shen, Software engineeringMetrics and Models (Redwood City, CA, USA: Benjamin/Cummings Publishing Company, 1986).
  40. [40] M. Jørgensen, Regression models of software development effortestimation accuracy and bias, Journal of Empirical SoftwareEngineering, 9(4), 2004, 297–314.

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