@article {10.3844/jcssp.2008.571.577,
article_type = {journal},
title = {An Empirical Validation of Object-Oriented Design Metrics for Fault Prediction },
author = {Xu, Jie and Ho, Danny and Capretz, Luiz F.},
volume = {4},
number = {7},
year = {2008},
month = {Jul},
pages = {571-577},
doi = {10.3844/jcssp.2008.571.577},
url = {https://thescipub.com/abstract/jcssp.2008.571.577},
abstract = {Problem Statement: Object-oriented design has become a dominant method in software industry and many design metrics of object-oriented programs have been proposed for quality prediction, but there is no well-accepted statement on how significant those metrics are. In this study, empirical analysis is carried out to validate object-oriented design metrics for defects estimation. Approach: The Chidamber and Kemerer metrics suite is adopted to estimate the number of defects in the programs, which are extracted from a public NASA data set. The techniques involved are statistical analysis and neuro-fuzzy approach. Results: The results indicate that SLOC, WMC, CBO and RFC are reliable metrics for defect estimation. Overall, SLOC imposes most significant impact on the number of defects. Conclusions/Recommendations: The design metrics are closely related to the number of defects in OO classes, but we can not jump to a conclusion by using one analysis technique. We recommend using neuro-fuzzy approach together with statistical techniques to reveal the relationship between metrics and dependent variables, and the correlations among those metrics also have to be considered.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}