Machine learning augmented diagnostic testing to identify sources of variability in test performance.
Christopher J. BanksAeron R. SanchezVicki StewartKate BowenGraham SmithRowland R. KaoPublished in: CoRR (2024)
Keyphrases
- machine learning
- test cases
- software testing
- test sequences
- test generation
- test data
- test suite
- regression testing
- statistical tests
- test case generation
- decision making
- databases
- testing process
- machine learning algorithms
- information sources
- expert systems
- data mining
- computer science
- pattern recognition
- learning algorithm
- machine learning and data mining
- usability testing
- medical diagnosis
- feature selection
- test data generation
- statistical methods
- diagnostic tests
- decision trees
- data sets
- text classification
- information extraction
- neural network
- clinical diagnosis
- code coverage
- model based testing
- number of test cases
- information retrieval
- set of test cases
- artificial intelligence
- computer vision
- statistical significance
- inductive learning
- knowledge sources
- learning tasks
- machine learning methods
- case study
- semi supervised learning
- model selection
- text mining
- data sources