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An Empirical Exploration of the Distributions of the Chidamber and Kemerer Object-Oriented Metrics Suite

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Abstract

The object-oriented metrics suite proposed by Chidamber and Kemerer (CK) is a measurement approach towards improved object-oriented design and development practices. However, existing studies evidence traces of collinearity between some of the metrics and low ranges of other metrics, two facts which may endanger the validity of models based on the CK suite. As high correlation may be an indicator of collinearity, in this paper, we empirically determine to what extent high correlations and low ranges might be expected among CK metrics.

To draw as much general conclusions as possible, we extract the CK metrics from a large data set (200 public domain projects) and we apply statistical meta-analysis techniques to strengthen the validity of our results. Homogenously through the projects, we found a moderate (∼0.50) to high correlation (>0.80) between some of the metrics and low ranges of other metrics.

Results of this empirical analysis supply researchers and practitioners with three main advises: a) to avoid the use in prediction systems of CK metrics that have correlation more than 0.80 b) to test for collinearity those metrics that present moderate correlations (between 0.50 and 0.60) c) to avoid the use as response in continuous parametric regression analysis of the metrics presenting low variance. This might therefore suggest that a prediction system may not be based on the whole CK metrics suite, but only on a subset consisting of those metrics that do not present either high correlation or low ranges.

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References

  • Aron, A., and Aron, E. N. 1997. Statistics for the Behavioral and Social Sciences. Prentice Hall.

  • Barnston, A. G. 1994. Linear statistical short-term climate predictive skill in the northern hemisphere. J. Climate 7: 1513-1564.

    Google Scholar 

  • Basili, V. R., Briand, L. C., and Melo, W. L. 1996. A validation of object-oriented design metrics as quality indicators. IEEE Trans. Softw. Eng. 22(10): October, 751-761.

    Google Scholar 

  • Belanger, S. E. 1997. Literature review and analysis of biological complexity in model stream ecosystems: Influence of size and experimental design. Eco. Environ. Saf. 36(1): 1-16.

    Google Scholar 

  • Belsley, D. A. 1991. Conditioning Diagnostics: Collinearity and Weak Data in Regression. New York: J. Wiley.

    Google Scholar 

  • Briand, L., and Wüst, J. 2001. Modeling development effort in object-oriented systems using design properties. IEEE Trans. Softw. Eng. 27(11): November, 963-986.

    Google Scholar 

  • Briand, L., Ikonomovski, S. V., and Lounis, H. 1999. Investigating quality factors in object-oriented designs: An industrial case study. Proc. 21st Int. Conf. on Softw. Eng. Los Angeles, May 16–22, 345-354.

  • Briand, L., Melo, W., and Wüst, J. 2002. Assessing the applicability of fault-proneness models across object-oriented software projects. IEEE Trans. Softw. Eng. 28(7): July, 706-720.

    Google Scholar 

  • Cartwright, M., and Shepperd, M. 2000. An empirical investigation of an object-oriented software system. IEEE Trans. Softw. Eng. 26(8): August, 786-796.

    Google Scholar 

  • Chidamber, S. R., and Kemerer, C. F. 1994. A metrics suite for object-oriented design. IEEE Trans. Softw. Eng. 20(6): June, 476-493.

    Google Scholar 

  • Chidamber, S. R., and Kemerer, C. F. 1991. Towards a metrics suite for object oriented design, Proceedings of the 6th ACM Conference on Object-Oriented Programming, Systems Languages, and Applications (OOPSLA'91), Phoenix, AZ, pp. 197-211.

  • Chidamber, S. R., Darcy, D. P., and Kemerer, C. F. 1998. Managerial use of metrics for object-oriented software: An exploratory analysis. IEEE Trans. Softw. Eng. 24(8): August, 629-639.

    Google Scholar 

  • Churcher, N., and Shepperd, M. J. 1995. Comments on “A metrics suite for object oriented design”. IEEE Trans. Softw. Eng. 21(3): March, 263-265.

    Google Scholar 

  • Cohen, J. 1977. Statistical Power Analysis for the Behavioral Sciences. New York: Academic Press.

    Google Scholar 

  • Cook, T. D., Cooper H., Cordray D. S., Hartmann H., Hedges L. V., Light R. J., Louis T. A., and Mosteller F. 1994. Meta-Analysis for explanation--A casebook.

  • Cooper, H. M., and Hedges, L. V. (eds.) 1994. The Handbook of Research Synthesis. New York: The Russell Sage Foundation.

    Google Scholar 

  • Daly, J., Brooks, A., Miller, J., Roper, M., and Wood, M. 1996. Evaluating inheritance depth on the maintainability of object-oriented software. Empir. Soft. Eng. 1(2): 109-132.

    Google Scholar 

  • El Emam, K., Benlarbi, S., and Goel, N. 1999. The confounding effect of class size on the validity of object-oriented metrics. Technical Report, NRC/ERB-1062, September.

  • El Emam, K., Melo, W., and Machado, J. C. 2001. The prediction of faulty classes using object-oriented metrics. J. Syst. Softw. 56(1): 63-75.

    Google Scholar 

  • Fenton, N. E., and Neil, M. 1999. A critique of software defect prediction models. IEEE Trans. Softw. Eng. 25(5): September/October, 675-689.

    Google Scholar 

  • Harrison, R., Counsell, S., and Nithi, R. 1998. Coupling metrics for object-oriented design. Proc. 5th Int. Symp. Softw. Metr. Bethesda Maryland, November.

  • Hayes, W. 2000. Research synthesis in software engineering: A case for meta-analysis. Proc. 6th IEEE Int. Symp. Softw. Metr. Boca-Raton, Florida, USA, November.

  • Hedges, L. V., and Olkin, I. 1985. Statistical Methods for Meta-Analysis. Orlando: Academic Press.

    Google Scholar 

  • Henderson-Sellers, B., Constantine, L. L., and Graham, I. M. 1996. Coupling and cohesion (towards a valid metrics suite for object-oriented analysis and design). Object Oriented Syst. 3(3): 143-158.

    Google Scholar 

  • Hitz, M., and Montazeri, B. 1996. Chidamber and Kemerer's metrics suite: A measurement theory perspective. IEEE Trans. Softw. Eng. 22(4): 267-271.

    Google Scholar 

  • Hu, Q. 1997. Evaluating alternative software production functions. IEEE Trans. Softw. Eng. 23(6): June, 379-387.

    Google Scholar 

  • Hunter, J. E., and Schmidt, F. L. 1990. Methods for Meta-Analysis: Correcting Error and Bias in Research Findings. Newbury Park, CA: Sage.

    Google Scholar 

  • Kendall, M. G. 1949. Rank and product-moment correlation. Biometrika 36: 177-193.

    Google Scholar 

  • Kendall, M. G., and Gibbons, J. D. 1990. Rank Correlation Methods, 5th edition. New York: Oxford University Press.

    Google Scholar 

  • Li, W., and Henry, S. 1993. Object-oriented metrics that predict maintainability. J. Syst. Softw. 23: 111-122.

    Google Scholar 

  • Liao, Yuen-Kuang Cliff. 1998. Effects on hypermedia versus traditional instruction on students' achievement: A meta-analysis. J. Res. Comput. Educ. 30(4): 341-359.

    Google Scholar 

  • Lloyd, C. J. 1999. Statistical Analysis of Categorical Data. Wiley-Interscience.

  • Miller, J. 2000. Can results from software engineering experiments be safely combined? Proc. 6th IEEE Int. Symp. Softw. Metr. Boca-Raton, Florida, USA, November.

  • Mišić, V. B., and Tešić, D. N. 1997. Estimation of effort and complexity: An object-oriented case study. J. Syst. Softw. 41(2): 133-143.

    Google Scholar 

  • Nesi, P., and Querci, T. 1998. Effort estimation and prediction of object-oriented systems. J. Syst. Softw. 42(1): 89-102.

    Google Scholar 

  • Pearson, K. 1907. Mathematical contributions to the theory of evolution. XVI. On further methods of deter-mining correlation. Drapers' Company Research Memoirs (Biometric Series 4). Cambridge University Press.

  • Pickard, L. M., Kitchenham, B. A., and Jones, P. W. 1998. Combining empirical results in software engineering. Inf. Softw. Technol. 40(14): 811-821.

    Google Scholar 

  • Ronchetti, M., and Succi, G. 1999. Early estimation of software size in object-oriented environments a case study in a CMM level 3 software firm. Submitted to IEEE Trans. Softw. Eng.

  • Rosenthal, R. 1991. Meta-Analytical Procedures for Social Research, Revised edition. Newbury Park, CA: Sage.

    Google Scholar 

  • Rupinski, M. T., and Dunlap, W. P. 1996. Approximating Pearson product-moment correlations from Kendall's tau and Spearman's rho. Educ. Psychol. Meas. 56(3): 419-429.

    Google Scholar 

  • Succi, G., Benedicenti, L., Bonamico, C., and Vernazza, T. 1998. The Webmetrics project--exploiting software tools on demand. World Multiconference on Systemics, Cybernetics, and Informatics. Orlando, FL.

  • Tang, M. H., Kao, M. H., and Chen, M. H. 1998. An empirical study on object-oriented metrics. Proc. 6th IEEE Int. Symp. Softw. Metr. Boca-Raton, Florida, USA, November.

  • Wood, M., Daly, J., Miller, J., and Roper, M. 1999. Multi-method research: An empirical investigation of object-oriented technology. J. Syst. Softw. 48(1): 13-26.

    Google Scholar 

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Authors and Affiliations

  1. Center for Applied Software Engineering, Free University of Bolzano-Bozen, Bolzano-Bozen, Italy

    Giancarlo Succi, Paolo Zuliani & Barbara Russo

  2. Department of Electrical and Computer Engineering, University of Alberta, Alberta, Canada

    Witold Pedrycz & Snezana Djokic

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  1. Giancarlo Succi
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  2. Witold Pedrycz
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  3. Snezana Djokic
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  4. Paolo Zuliani
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  5. Barbara Russo
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Succi, G., Pedrycz, W., Djokic, S. et al. An Empirical Exploration of the Distributions of the Chidamber and Kemerer Object-Oriented Metrics Suite. Empirical Software Engineering 10, 81–104 (2005). https://doi.org/10.1023/B:EMSE.0000048324.12188.a2

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