Improving Predictive Models of Software Quality Using an Evolutionary Computational Approach
Rodrigo A. Vivanco · Proceedings/Proceedings - Conference on Software Maintenance · 2007
Predictive models can be used to identify components as potentially problematic for future maintenance. Source code metrics can be used as input features to classifiers, however, there exist a large number of structural measures that capture different aspects of coupling, cohesion, inheritance, complexity and size. Feature selection is the process of identifying a subset of attributes that improves a classifier's performance. The focus of this study is to explore the efficacy of a genetic algorithm as a method of improving a classifier's ability to identify problematic components.