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How We Refactor and How We Document it? On the Use of Supervised Machine Learning Algorithms to Classify Refactoring Documentation
To cope with the above-mentioned limitations, we aim to better understand what motivates developers to apply refactoring by mining and classifying a large set of 111, 884 commits containing refactorings, extracted from 800 Java projects.
Toward the Automatic Classification of Self-Affirmed Refactoring
In this paper, we propose a two-step approach to first identify whether a commit describes developer-related refactoring events, then to classify it according to the refactoring common quality improvement categories.
Do Design Metrics Capture Developers Perception of Quality? An Empirical Study on Self-Affirmed Refactoring Activities
We aim at identifying, among the various quality models presented in the literature, the ones that are more in-line with the developer's vision of quality optimization, when they explicitly mention that they are refactoring to improve them.
