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
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
Exploring the relationship between design measures and software quality in object-oriented systems
Journal of Systems and Software
Data mining: concepts and techniques
Data mining: concepts and techniques
The Confounding Effect of Class Size on the Validity of Object-Oriented Metrics
IEEE Transactions on Software Engineering
Comparing Software Prediction Techniques Using Simulation
IEEE Transactions on Software Engineering - Special section on the seventh international software metrics symposium
A Unified Framework for Cohesion Measurement in Object-OrientedSystems
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
A Neuro-Fuzzy Model for Software Cost Estimation
QSIC '03 Proceedings of the Third International Conference on Quality Software
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
Data Mining Static Code Attributes to Learn Defect Predictors
IEEE Transactions on Software Engineering
Empirical Analysis of Object-Oriented Design Metrics for Predicting High and Low Severity Faults
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering
Software Structure Metrics Based on Information Flow
IEEE Transactions on Software Engineering
IEEE Transactions on Neural Networks
Hi-index | 0.00 |
Importance of construction of models for predicting software quality attributes is increasing leading to usage of artificial intelligence techniques such as Artificial Neural Network (ANN). The goal of this paper is to empirically compare traditional strategies such as Logistic Regression (LR) and ANN to assess software quality. The study used data collected from public domain NASA data set. We find the effect of software metrics on fault proneness. The fault proneness models were predicted using LR regression and ANN methods. The performance of the two methods was compared by Receiver Operating Characteristic (ROC) analysis. The areas under the ROC curves are 0.78 and 0.745 for the LR and ANN model, respectively. The predicted model shows that software metrics are related to fault proneness. The models predict faulty classes with more than 70 percent accuracy. The study showed that ANN method can also be used in constructing software quality models and more similar studies should further investigate the issue. Based on these results, it is reasonable to claim that such a model could help for planning and executing testing by focusing resources on fault-prone parts of the design and code.