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Empirical analysis of CK metrics for object-oriented design complexity: implications for software defects
Abstract
To produce high quality object-oriented (OO) applications, a strong emphasis on design aspects, especially during the early phases of software development, is necessary. Design metrics play an important role in helping developers understand design aspects of software and, hence, improve software quality and developer productivity. In this paper, we provide empirical evidence supporting the role of OO design complexity metrics, specifically a subset of the Chidamber and Kemerer (1991, 1994) suite (CK metrics), in determining software defects. Our results, based on industry data from software developed in two popular programming languages used in OO development, indicate that, even after controlling for the size of the software, these metrics are significantly associated with defects. In addition, we find that the effects of these metrics on defects vary across the samples from two programming languages-C++ and Java. We believe that these results have significant implications for designing high-quality software products using the OO approach.
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Cites
Regression Diagnostics: Identifying Influential Data and Sources of Collinearity
Belsley, D. A., Kuh, E., & Welsch, R. E. (1980) · Wiley Series in Probability and Statistics · doi:10.1002/0471725153 · Cited by 7,297
Cited by
Predicting defects using network analysis on dependency graphs
Zimmermann, T., & Nagappan, N. (2008) · Proceedings of the 13th international conference on Software engineering - ICSE '08 · doi:10.1145/1368088.1368161 · Cited by 580
Software fault prediction metrics: A systematic literature review
Radjenović, D., Heričko, M., Torkar, R., & Živkovič, A. (2013) · Information and Software Technology · doi:10.1016/j.infsof.2013.02.009 · Cited by 538
Revisiting the Impact of Classification Techniques on the Performance of Defect Prediction Models
Ghotra, B., McIntosh, S., & Hassan, A. E. (2015) · 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering · doi:10.1109/icse.2015.91 · Cited by 364
An empirical study on software defect prediction with a simplified metric set
He, P., Li, B., Liu, X., Chen, J., & Ma, Y. (2015) · Information and Software Technology · doi:10.1016/j.infsof.2014.11.006 · Cited by 309
Olague, H. M., Etzkorn, L. H., Gholston, S., & Quattlebaum, S. (2007) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2007.1015 · Cited by 304
Metadata
- Authors
- Subramanyam, R., & Krishnan, M. S.
- Venue
- IEEE Transactions on Software Engineering
- Published
- 2003-04
- Volume
- 29
- Issue
- 4
- Pages
- 297-310
- ISSN
- 0098-5589 (ISSN-L)
- OpenAlex
- W2107643286
- Cited by
- 672
- References
- 1
- FWCI
- 51.12
- Type
- journal article
- Language
- en
- Open access
- closed
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- Subramanyam, R., & Krishnan, M. S. (2003). Empirical analysis of CK metrics for object-oriented design complexity: implications for software defects. IEEE Transactions on Software Engineering. https://doi.org/10.1109/tse.2003.1191795
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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