The Confounding Effect of Class Size on the Validity of Object-Oriented Metrics
IEEE Transactions on Software Engineering
Object-oriented metrics: A review of theory and practice
Advances in software engineering
Metrics for maintainability of class inheritance hierarchies
Journal of Software Maintenance: Research and Practice
Measuring OO Design Metrics from UML
UML '02 Proceedings of the 5th International Conference on The Unified Modeling Language
IEEE Transactions on Software Engineering
Thresholds for Object-Oriented Measures
ISSRE '00 Proceedings of the 11th International Symposium on Software Reliability Engineering
A relational approach to software metrics
Proceedings of the 2004 ACM symposium on Applied computing
Investigation into the exploitation of Object-Oriented features
ACM SIGSOFT Software Engineering Notes
Toward a Software Testing and Reliability Early Warning Metric Suite
Proceedings of the 26th International Conference on Software Engineering
Empirical Software Engineering
Static analysis tools as early indicators of pre-release defect density
Proceedings of the 27th international conference on Software engineering
Application of neural networks for software quality prediction using object-oriented metrics
Journal of Systems and Software
Early estimation of defect density using an in-process Haskell metrics model
A-MOST '05 Proceedings of the 1st international workshop on Advances in model-based testing
Early estimation of software quality using in-process testing metrics: a controlled case study
3-WoSQ Proceedings of the third workshop on Software quality
Object-oriented software fault prediction using neural networks
Information and Software Technology
Towards a generic model for software quality prediction
Proceedings of the 6th international workshop on Software quality
Journal of Systems and Software
Iterative identification of fault-prone binaries using in-process metrics
Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement
Application of support vector machine to predict fault prone classes
ACM SIGSOFT Software Engineering Notes
Estimating software readiness using predictive models
Information Sciences: an International Journal
Fault detection and prediction in an open-source software project
PROMISE '09 Proceedings of the 5th International Conference on Predictor Models in Software Engineering
International Journal of Computer Applications in Technology
Empirical validation of object-oriented metrics for predicting fault proneness models
Software Quality Control
On the ability of complexity metrics to predict fault-prone classes in object-oriented systems
Journal of Systems and Software
Tracking the evolution of object-oriented quality metrics on agile projects
XP'07 Proceedings of the 8th international conference on Agile processes in software engineering and extreme programming
An empirical evaluation of coupling metrics on aspect-oriented programs
Proceedings of the 2010 ICSE Workshop on Emerging Trends in Software Metrics
Towards identifying software project clusters with regard to defect prediction
Proceedings of the 6th International Conference on Predictive Models in Software Engineering
Assessment of usability metrics for object-oriented software system
ACM SIGSOFT Software Engineering Notes
Assessment of maintainability metrics for object-oriented software system
ACM SIGSOFT Software Engineering Notes
Software fault prediction for object oriented systems: a literature review
ACM SIGSOFT Software Engineering Notes
ACM SIGSOFT Software Engineering Notes
Defect proneness estimation and feedback approach for software design quality improvement
Information and Software Technology
Reducing test effort: A systematic mapping study on existing approaches
Information and Software Technology
Software fault prediction with object-oriented metrics based artificial immune recognition system
PROFES'07 Proceedings of the 8th international conference on Product-Focused Software Process Improvement
Component-based software certification based on experimental risk assessment
LADC'07 Proceedings of the Third Latin-American conference on Dependable Computing
Empirical evaluation of the effects of mixed project data on learning defect predictors
Information and Software Technology
Empirical evidence on OCL formal specification-based metrics as a predictor of fault-proneness
ACM SIGSOFT Software Engineering Notes
Comparative study on effectiveness of standard bug prediction approaches
Proceedings of the 5th IBM Collaborative Academia Research Exchange Workshop
Investigating of high and low impact faults in object-oriented projects
ACM SIGSOFT Software Engineering Notes
An in-depth study of the potentially confounding effect of class size in fault prediction
ACM Transactions on Software Engineering and Methodology (TOSEM)
A comparative study of models for predicting fault proneness in object-oriented systems
International Journal of Computer Applications in Technology
Applications of fuzzy integrals for predicting software fault-prone
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
| Hi-index | 0.00 |
The objective of this study is the investigation of the correlation between object-oriented design metrics and the likelihood of the occurrence of object-oriented faults. Such a relationship, if identified, can be utilized to select effective testing techniques that take the characteristics of the program under test into account.Our empirical study was conducted on three industrial real-time systems that contain a number of natural faults reported for the past three years. The faults found in these three systems are classified into three types: object-oriented faults, object management faults and traditional faults. The object-oriented design metrics suite proposed by Chidamber and Kemerer is validated using these faults. Moreover, we propose a set of new metrics that can serve as an indicator of how strongly object-oriented a program is, so that the decision to adopt object-oriented testing techniques can be made, to achieve more reliable testing and yet minimize redundant testing efforts.