Recommending adaptive changes for framework evolution
Proceedings of the 30th international conference on Software engineering
On the relation of refactorings and software defect prediction
Proceedings of the 2008 international working conference on Mining software repositories
Automatically identifying changes that impact code-to-design traceability during evolution
Software Quality Control
Linking software design metrics to component change-proneness
Proceedings of the 2nd International Workshop on Emerging Trends in Software Metrics
Predicting the maintainability of XSL transformations
Science of Computer Programming
Recommending Adaptive Changes for Framework Evolution
ACM Transactions on Software Engineering and Methodology (TOSEM)
Issues arising from refactoring studies: an experience report
ACM SIGSOFT Software Engineering Notes
Is it dangerous to use version control histories to study source code evolution?
ECOOP'12 Proceedings of the 26th European conference on Object-Oriented Programming
Data stream mining for predicting software build outcomes using source code metrics
Information and Software Technology
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Can we predict locations of future refactoring based on the development history? In an empirical study of open source projects we found that attributes of software evolution data can be used to predict the need for refactoring in the following two months of development. Information systems utilized in software projects provide a broad range of data for decision support. Versioning systems log each activity during the development, which we use to extract data mining features such as growth measures, relationships between classes, the number of authors working on a particular piece of code, etc. We use this information as input into classification algorithms to create prediction models for future refactoring activities. Different state-of-the-art classifiers are investigated such as decision trees, logistic model trees, propositional rule learners, and nearest neighbor algorithms. With both high precision and high recall we can assess the refactoring proneness of object-oriented systems. Although we investigate different domains, we discovered critical factors within the development life cycle leading to refactoring, which are common among all studied projects.