Intelligent Automation Practices for API Testing: Enhancing Efficiency and Quality
The article outlines how intelligent automation—leveraging data‑driven algorithms for automated case generation, dynamic execution, diff‑based result analysis, noise reduction, failure diagnosis, and effectiveness evaluation—addresses API testing challenges such as manual case writing, low efficiency, redundancy, and reliability, ultimately boosting automation ratios, cutting long‑tail tasks, and enhancing test efficiency and quality.
