Sara Filipa Fernandes

Abstract
Refactoring helps to improve the design of software systems, making them more readable, maintainable, cleaner, and easy to expand. Most of the tools that already exist on this concept allow developers to select and execute the best refactoring techniques for a particular programming context. However, they aren't interactive and prompt enough, providing a poor programming experience. In this gap, we can introduce and combine the topic of liveness with refactoring methods. Live Refactoring allows to know continuously, while programming, the blocks of code that we should refactor and why they were classified as problematic. Therefore, it shortens the time needed to create high-quality systems, due to early and continuous refactoring feedback, support, and guidance. This paper presents our research project based on a live refactoring environment. This environment is focused on a refactoring tool that aims to explore the concept of Live Refactoring and its main components-recommendation, visualization, and application. © 2021 Owner/Author.

Abstract

Abstract

Abstract
With the increasing complexity of software systems, software developers would benefit from instant and continuous guidance about the system they are maintaining and evolving. Despite existing several solutions providing feedback and suggesting improvements, many tools require explicit invocation, leading to developers missing improvement opportunities, such as important refactorings, due to lost of train of thought. Therefore, to address these limitations, we propose an approach where developers receive instant and continuous feedback about their software systems. This guidance would include the detection of code smells and the suggestion of refactorings to improve the system, justified by relevant software quality metrics related to the recommendations. This research aims to improve the experience of developing and maintaining software systems by providing a live environment for continuous inspection and refactoring of software systems, that is informative, responsive, and tactically predictive, and thus helping developers to identify and solve quality problems in a quicker and better way.