Prediction of software fault-prone classes using ensemble random forest with adaptive synthetic sampling algorithm.
A. BalaramS. VasundraPublished in: Autom. Softw. Eng. (2022)
Keyphrases
- random forest
- sampling algorithm
- fault prone
- software modules
- ensemble methods
- software quality
- ensemble classifier
- prediction accuracy
- source code
- random sampling
- decision trees
- ensemble learning
- software metrics
- feature set
- software development
- software systems
- fold cross validation
- base classifiers
- development effort
- markov chain monte carlo
- feature ranking
- software projects
- software components
- multi label
- software engineering
- neural network
- open source
- learning algorithm
- evolutionary algorithm
- feature extraction
- reinforcement learning
- higher order