A Unified Framework for Coupling Measurement in Object-Oriented Systems
IEEE Transactions on Software Engineering
Object-oriented metrics: A review of theory and practice
Advances in software engineering
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
A Unified Framework for Cohesion Measurement in Object-OrientedSystems
Empirical Software Engineering
A Metrics Suite for Object Oriented Design
IEEE Transactions on Software Engineering
Survey: A survey on search-based software design
Computer Science Review
Search-based software engineering: Trends, techniques and applications
ACM Computing Surveys (CSUR)
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Predictive models can be used to discover potentially problematic components. Source code metrics can be used as input features to predictive models, however, there are many structural and design measures that capture related metrics of coupling, cohesion, inheritance, complexity and size. Feature selection is the process of identifying a subset of attributes that improves the performance of a predictive model. This paper presents a prototype that implements a parallel genetic algorithm as a search-based feature selection method that enhances a predictive model's ability to identify cognitively complex components in a Java application.