Overview of ways to automate the refactoring of code clones

DOI: 10.31673/2412-9070.2024.050575

Abstract

The modern development of technologies in the field of software engineering requires constant efforts in optimizing and improving code quality. One of the pressing issues is the presence of code clones, which can lead to errors and complicate the further maintenance of software systems. Automating the refactoring of code clones is of significant interest to researchers and practitioners in this field.
The main tasks of the research cover several key aspects. First and foremost, the research focuses on an in-depth analysis of existing methods and techniques already used for automating clone refactoring. This includes studying the effectiveness of existing approaches and identifying their limitations. An important part is the analysis of algorithms that can improve the accuracy of clone detection and the efficiency of their refactoring. Moreover, the research analyzes the impact of automation on the quality and maintainability of software systems, helping to determine how such technologies can be integrated into real software development projects.
The study aims to identify the limitations of current approaches and propose ways to optimize them, considering the modern technological capabilities and needs of the software market. The research includes a critical review of the literature, the study of reports on the application of tools in practice, and the analysis of the results of using automated systems in real projects. This allows for the evaluation of the effectiveness of various algorithms and methods for detecting and refactoring code clones, as well as their impact on the quality of the final product and the efficiency of development. The conclusions proposed within the study will include recommendations for addressing identified gaps in current methods and suggesting a new approach to the automation of clone refactoring that can provide greater adaptability and efficiency.

Keywords: code clones, automation of refactoring, machine learning, static analysis, code optimization, code quality