LLM-Powered Unit Testing: Writing Reliable Java Tests with AI Assistance
summary
Shows how to use Large Language Models (OpenAI, Claude, GitHub Copilot) to generate, validate, and scale Java unit tests. Covers prompt design, validation layers, CI/IDE automation, and integration with tools like SonarQube and JaCoCo, plus practical Java examples and live demos of generating meaningful test cases and evaluating AI-generated tests' strengths and limits.
AI-written summary · about
chapters (5)
- 0:00Introduction
- 3:55AI-assisted unit testing
- 8:28Prompt engineering for tests
- 14:00Results and adoption
- 19:58Key takeaways
related talks
47mTDD & Generative AI: A Perfect Pairing
46mGenerative AI in Practice: Concrete Use Cases for an LLM in Java
46mAI-powered Java Developers
15mUsing AI effectively in large Java codebases
48mTDD & generative AI - a perfect pairing?
58mAI Assistant: Don’t Code Alone
45mWhere AI Meets Code
25mAI vs. AI: How to Test AI Systems Using AI