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
Managerial Use of Metrics for Object-Oriented Software: An Exploratory Analysis
IEEE Transactions on Software Engineering
A Critique of Software Defect Prediction Models
IEEE Transactions on Software Engineering
A Metrics Suite for Object Oriented Design
IEEE Transactions on Software Engineering
Using Metrics to Predict OO Information Systems Maintainability
CAiSE '01 Proceedings of the 13th International Conference on Advanced Information Systems Engineering
Predicting Testability of Program Modules Using a Neural Network
ASSET '00 Proceedings of the 3rd IEEE Symposium on Application-Specific Systems and Software Engineering Technology (ASSET'00)
A Study on Fault-Proneness Detection of Object-Oriented Systems
CSMR '01 Proceedings of the Fifth European Conference on Software Maintenance and Reengineering
Application of neural networks for software quality prediction using object-oriented metrics
Journal of Systems and Software
Proceedings of the 2006 international workshop on Software quality
IEEE Transactions on Neural Networks
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To accomplish software quality, correct estimation of maintainability is essential. However there is a complex and non-linear relationship between object-oriented metrics and maintainability. Thus maintainability of object-oriented software can be predicted by applying sophisticated modeling techniques like artificial neural network. Multilayer Perceptron neural network is chosen for the present study because of its robustness and adaptability. This paper presents the prediction of maintainability by using a Multilayer Perceptron (MLP) model and compares the results of this investigation with other models described earlier. It is found that efficacy of MLP model is much better than both Ward and GRNN network models.