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The introduction presents the problem: legacy refactoring requires manual skills that many developers lack. Emerging tools like GitHub Copilot, Amazon CodeWhisperer, and Tabnine are reshaping the landscape. These models, tailored for technological automation, offer fast solutions but demand critical precision. Practical examples show how these tools reduce development time and improve code quality. Through case study analysis and technology comparisons, it becomes clear that results depend on specific requirements such as code complexity and familiarity with the tools. Developers should integrate them gradually while maintaining constant oversight. For a practical guide, it's recommended to test each solution on pilot projects. With dedication, these tools can transform traditional processes into simple and effective operations.

Frequently Asked Questions

Which LLM is best suited for legacy refactoring?

GitHub Copilot is often preferred for its integration with Git and its precision within the context of existing projects, while Amazon CodeWhisperer excels in complex enterprise environments. Tabnine offers flexibility but requires greater caution to avoid errors.

How can these tools be integrated into existing workflows?

Start with pilot projects and gradually update development practices. Ongoing training and rigorous testing are essential for achieving sustainable results.