A Rule-Learning Approach for Detecting Faults in Highly Configurable Software Systems from Uniform Random Samples.
Ruben HeradioDavid Fernández-AmorósVictoria RuizManuel J. CoboPublished in: HICSS (2022)
Keyphrases
- software systems
- rule learning
- random samples
- random sampling
- software engineering
- subgroup discovery
- standard deviation
- uniform distribution
- sample size
- inductive logic programming
- source code
- decision rules
- rule sets
- software development
- inductive learning
- multi agent systems
- random projections
- random sample
- learning classifier systems
- relational learning
- multi agent
- active learning
- hill climbing
- learning scheme
- neural network