Genetic Algorithms for Optimizing Ensemble of Models in Software Reliability Prediction
Explore this paper's citation graph
Summary
Genetic Algorithms (GA) is explored as an alternative approach to derive software reliability models by evaluating the predictive capability of the developed ensemble of models and the results were compared with traditional models.
- Type
- article
- Published
- 2008-01-01
- Cited by
- 0
- References
- 27
- OpenAlex
- https://openalex.org/W43897323
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:267820942
Keywords
Computer science, Machine learning, Reliability (semiconductor), Software, Software quality
References
- Predicting Accumulated Faults in Software Testing Process Using Radial Basis Function Network Models
- Software reliability forecasting by support vector machines with simulated annealing algorithms
- Software Reliability Engineering: More Reliable Software Faster and Cheaper
- Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence
- Multiple Classifier Systems
- Optimal linear combinations of neural networks: an overview
- Reliability Growth Modeling for Software Fault Detection Using Particle Swarm Optimization
- Prediction of software reliability: a comparison between regression and neural network non-parametric models
- A theory of software reliability and its application
- A critical review on software reliability modeling
- Using Boosting Techniques to Improve Software Reliability Models Based on Genetic Programming
- A study of the connectionist models for software reliability prediction
- On-line prediction of software reliability using an evolutionary connectionist model
- Neural-network-based approaches for software reliability estimation using dynamic weighted combinational models
- An introduction to genetic algorithms
- Neural Network Modeling for Software Reliability Prediction from Failure Time Data
- Estimation of the COCOMO Model Parameters Using Genetic Algorithms for NASA Software Projects
- Modeling software reliability growth with genetic programming
- Prediction of Software Reliability Using Connectionist Models
- Evolutionary neural network modeling for software cumulative failure time prediction
Cited by
Related papers
- Modeling software reliability growth with genetic programming
- A study of applying support vector machine and Genetic Algorithm to software reliability forecasting
- An empirical study of software reliability prediction using machine learning techniques
- Software Reliability Assessment: Modeling and Algorithms
- A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models: a Search-Based Software Engineering Approach
- Software Reliability Prediction using Neural Network with Encoded Input
- Enrichment of antioxidants in black garlic juice using macroporous resins and their protective effects on oxidation-damaged human erythrocytes.
- Software reliability modeling based on SVM and virtual sample
- Prediction of Software Reliability Using Feed Forward Neural Networks