Enhancing code quality through automated refactoring techniques

Resumen

In the context of the rapidly evolving field of software development, maintaining high code quality is of critical importance in order to ensure the long-term sustainability, maintainability, and scalability of software systems. This thesis examines the potential of automated refactoring techniques to enhance code quality and address the challenges posed by evolving software architectures.

The objective of this thesis is to develop and implement an automated refactoring tool within the IntelliJ IDEA integrated development environment. The tool will focus on streamlining codebases, fostering collaboration among development teams, and enhancing the resilience of software systems. The study aims to provide valuable insights for developers and organisations seeking to achieve superior code quality in the context of the rapid evolution of technology.

It is evident that there is a pressing need to comprehend the influence of automated refactoring on code quality, as existing manual methods may not be sufficiently effective in addressing the intricate aspects of modern software architecture.

The methodology entails a comprehensive analysis of existing literature and academic sources with the objective of gaining an understanding of automated refactoring methodologies. An empirical analysis is conducted on existing refactoring plugins, after which a new plugin tailored for the IntelliJ IDEA environment is developed.

The results indicate a notable enhancement in code quality, maintainability, and readability. Empirical analyses have demonstrated the plugin's effectiveness in identifying and correcting code smells and enhancing software structure. The thesis offers practical guidance for developers and organisations on the effective utilisation of automated refactoring tools within their workflows.

Automated refactoring is a highly effective tool for enhancing code quality and addressing the challenges of evolving software systems. This thesis advances the understanding of automated refactoring, contributing to the development of effective tools for maintaining and improving code quality in modern software development practices.