Long‑running tests are a common pain point in large codebases, draining developer focus, slowing feedback loops, and hindering rapid learning. While many established strategies exist to cut test times in small projects, they rarely suffice for enterprise‑grade Spring Boot applications. This talk will first revisit the fundamentals of test‑runtime optimization to set a shared baseline, then dive into advanced, predictive test‑execution techniques that scale. We’ll explore three key approaches—git‑diff‑based, dependency‑graph‑based, and machine‑learning‑based execution—to identify only the tests that need running. Participants will learn how to evaluate existing tools, weigh their trade‑offs, and decide which strategy fits their workflow. Practical guidance will cover integration into local development and CI pipelines, enabling teams to dramatically reduce test times and elevate developer productivity and satisfaction.