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Refactoring is essential for maintaining and modernizing Java applications, yet it often feels slow, risky, and time-consuming. While IDEs offer powerful refactoring tools, developers are often hesitant to use them without clear evidence of improvement. This session takes a data-driven approach to refactoring by demonstrating how to measure code quality before and after automated transformations. Through practical examples, attendees will see how to evaluate the impact of refactoring efforts, quantify improvements, and identify where automation can safely accelerate modernization. The goal is to refactor smarter, not just faster, achieving measurable gains in maintainability, performance, and developer productivity.
What You Will Learn
How to measure and evaluate code quality before and after refactoring
How to use automated code transformation tools effectively and safely
Techniques to balance modernization speed with long-term maintainability
Who Should Attend
Java developers, software engineers, and architects interested in applying data-driven techniques to refactor, modernize, and improve the quality of existing applications.