Towards a metrics suite for object oriented design
OOPSLA '91 Conference proceedings on Object-oriented programming systems, languages, and applications
Object-oriented metrics that predict maintainability
Journal of Systems and Software - Special issue on object-oriented software
Object-oriented software metrics: a practical guide
Object-oriented software metrics: a practical guide
A software complexity model of object-oriented systems
Decision Support Systems - Special issue on information technologies and systems
Cohesion and reuse in an object-oriented system
SSR '95 Proceedings of the 1995 Symposium on Software reusability
Machine Learning
Object-oriented metrics: measures of complexity
Object-oriented metrics: measures of complexity
A Validation of Object-Oriented Design Metrics as Quality Indicators
IEEE Transactions on Software Engineering
An Evaluation of the MOOD Set of Object-Oriented Software Metrics
IEEE Transactions on Software Engineering
Managerial Use of Metrics for Object-Oriented Software: An Exploratory Analysis
IEEE Transactions on Software Engineering
A Unified Framework for Coupling Measurement in Object-Oriented Systems
IEEE Transactions on Software Engineering
Proceedings of the 20th international conference on Software engineering
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Exploring the relationship between design measures and software quality in object-oriented systems
Journal of Systems and Software
The Confounding Effect of Class Size on the Validity of Object-Oriented Metrics
IEEE Transactions on Software Engineering
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
A Unified Framework for Cohesion Measurement in Object-OrientedSystems
Empirical Software Engineering
Replicated Case Studies for Investigating Quality Factorsin Object-Oriented Designs
Empirical Software Engineering
A Metrics Suite for Object Oriented Design
IEEE Transactions on Software Engineering
An Empirical Investigation of an Object-Oriented Software System
IEEE Transactions on Software Engineering
An Empirical Study on Object-Oriented Metrics
METRICS '99 Proceedings of the 6th International Symposium on Software Metrics
Empirical Validation of Object-Oriented Metrics on Open Source Software for Fault Prediction
IEEE Transactions on Software Engineering
Software Reuse Metrics for Object-Oriented Systems
SERA '05 Proceedings of the Third ACIS Int'l Conference on Software Engineering Research, Management and Applications
Empirical Analysis of Object-Oriented Design Metrics for Predicting High and Low Severity Faults
IEEE Transactions on Software Engineering
Fault Recognition with Labeled Multi-category Support Vector Machine
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 01
Empirical Analysis of Software Fault Content and Fault Proneness Using Bayesian Methods
IEEE Transactions on Software Engineering
Adapting a fault prediction model to allow inter languagereuse
Proceedings of the 4th international workshop on Predictor models in software engineering
Software Process: Improvement and Practice
A genetic algorithm to configure support vector machines for predicting fault-prone components
PROFES'11 Proceedings of the 12th international conference on Product-focused software process improvement
Assessment of software testing time using soft computing techniques
ACM SIGSOFT Software Engineering Notes
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Empirical validation of software metrics to predict quality using machine learning methods is important to ensure their practical relevance in the software organizations. It would also be interesting to know the relationship between object-oriented metrics and fault proneness. In this paper, we build a Support Vector Machine (SVM) model to find the relation-ship between object-oriented metrics given by Chidamber and Kemerer and fault proneness. The proposed model is empirically evaluated using open source software. The performance of the SVM method was evaluated by Receiver Operating Characteristic (ROC) analysis. Based on these results, it is reasonable to claim that such models could help for planning and performing testing by focusing resources on fault- prone parts of the design and code. Thus, the study shows that SVM method may also be used in constructing software quality models. However, similar types of studies are required to be carried out in order to establish the acceptability of the model.