Transforming Java Code Testing: Accelerating Success With AI

Presented by

Nathan Jakubiak - Sr Director of Development & Jamie Motheral, Enterprise Solutions Manager

About this talk

When AI is employed in code-level testing, including static analysis processes and unit testing, it provides developers with a multitude of advantages to enhance and expedite their quality assurance and testing efforts. From the viewpoint of management, these enhancements result in heightened efficiency in the development of new code and assist projects in adhering to their schedules and budget constraints for software deliveries. Join us on November 30 to learn about how solutions that leverage AI optimize and accelerate Java code testing practices and triage and remediate static analysis findings. Learn how AI and ML technologies: • Optimize static analysis triage workflows to accelerate violation remediation. • Enhance unit testing practices from test creation to test customization, maintenance, and execution. • Increase developer productivity to better deliver projects on time and on budget.
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