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National Science Foundation

Cyber-Physical Systems Virtual Organization

Read-only archive of site from September 29, 2023.

CPS-VO

supervised learning algorithms

biblio

Visible to the public Predicting Fault-Prone Classes in Object-Oriented Software: An Adaptation of an Unsupervised Hybrid SOM Algorithm

Submitted by grigby1 on Thu, 12/28/2017 - 1:30pm
  • software quality
  • Predictive Metrics
  • Predictive models
  • predictive security metrics
  • pubcrawl
  • self-organising feature maps
  • Self-Organizing Map
  • semisupervised fault-proneness prediction models
  • software metrics
  • Prediction algorithms
  • Software systems
  • source code (software)
  • supervised learning algorithms
  • Unsupervised Fault-Proneness Prediction
  • unsupervised fault-proneness prediction models
  • unsupervised hybrid SOM algorithm
  • Unsupervised Learning
  • Adaptation models
  • object-oriented software systems
  • object-oriented programming
  • Object-Oriented Metrics Threshold Values
  • Object oriented modeling
  • Naive Bayes Network
  • Multilayer Perceptron
  • Metrics
  • Measurement
  • HySOM model
  • function-level source code metrics
  • fault-prone code identification
  • fault-prone classes prediction model
  • fault data history
  • Data models
  • class-level granularity

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