Artificial Intelligence
Software metrics for reliability assessment
Handbook of software reliability engineering
A Critique of Software Defect Prediction Models
IEEE Transactions on Software Engineering
Designing Maintainable Software
Designing Maintainable Software
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
A Rule-Based Approach to Developing Software Development Prediction Models
Automated Software Engineering
Experience With the Accuracy of Software Maintenance Task Effort Prediction Models
IEEE Transactions on Software Engineering
Prediction Models for Software Fault Correction Effort
CSMR '01 Proceedings of the Fifth European Conference on Software Maintenance and Reengineering
Review: Software fault prediction: A literature review and current trends
Expert Systems with Applications: An International Journal
| Hi-index | 0.00 |
Software maintenance engineers need tools to support their work. To make such tools relevant, the tools should provide engineers with quantitative input, as well as the knowledge needed to understand those factors influencing maintenance activities. This paper proposes a comprehensive meta-model for the prediction of a number of defects; it dwells on evidence theory and a number of fuzzy-based models developed using different techniques applied to different subsets of data. Evidence theory and belief function values assigned to generated models are used for reasoning purposes. The study comprises a detailed case for estimating the number of defects in a medical imaging system.