Towards just-in-time rational refactoring

Code smells have been defined as symptoms of poor design and implementation choices. Empirical studies showed that code smells can have a negative impact on the maintainability of code. For this reason, tools have been developed to automatically detect design flaws and, in some cases, to recommend developers how to remove them via refactoring. However, these tools are not able to prevent the introduction of design flaws. This means that the code has to experience a quality decay before state-of-the-art tools can be applied. In addition, existing tools recommend refactoring operations that mostly target the improvement of quality metrics (e.g., cohesion) rather than the generation of refactorings that are meaningful from the developers' perspective. Our goal is to develop techniques serving as the basis for a new generation of refactoring recommenders able to (i) predict code components likely to be affected by code smells in the near future, to refactor them before they experience a quality decay and (ii) recommend meaningful refactorings emulating the ones that developers would perform, rather than the ones targeting the improvement of metrics. We refer to such a perspective on refactoring as just-in-time rational refactoring.