Towards Just-in-Time Refactoring Recommenders

Abstract

Empirical studies have provided ample evidence that low code quality is generally associated with lower maintainability. For this reason, tools have been developed to automatically detect design flaws (e.g., code smells). However, these tools are not able to prevent the introduction of design flaws. This means that the code has to experience a quality decay (with a consequent increase of maintenance/evolution costs) before state-of-the-art tools can be applied to identify and refactor the design flaws. Our goal is to develop a new generation of refactoring recommenders aimed at preventing, via refactoring operations, the introduction of design flaws rather than fixing them once they already affect the system. We refer to such a novel perspective on software refactoring as just-in-time refactoring. In this paper, we make a first step towards this direction, presenting an approach able to predict which classes will be affected in the future by code smells.