Hey everyone! I'm diving into AI-assisted coding and testing out different AI plugins and IDEs. While I've experienced decent success with AI generating code, I've noticed that when it comes to creating Jest unit tests, things get a bit off-track. I usually ask the AI to generate a test file for my services, but I end up with files filled with mocked methods that only test those mocks instead of the actual code logic. Am I missing something here? Are there specific prompts or techniques that you guys use to get more effective and meaningful Jest tests from AI? I'd love to hear your advice!
3 Answers
The effectiveness can really vary based on the programming language and the testing frameworks you're using. For instance, I've had fantastic outcomes with Rust and Python unit tests specifically from Claude. Having some experience helps too, as I've been figuring out how to use LLMs effectively since the early ChatGPT days. So there is definitely potential—just keep experimenting!
Honestly, I think even human-written unit tests often fall short! Since AI models learn from data that might not have perfect examples, it's a tall order to expect them to nail it on the first try. But with the right inputs and guidance, they can improve over time.
It's crucial to define your parameters clearly before you ask the AI to generate those tests. Make sure you have a solid specification for your application so the tests can be written against it properly. Have a good chat about which parts are okay to mock and which parts should be tested as is. I’ve had positive experiences with this approach, but it does require some hand-holding to get started. Once you build a routine, the AI can start recognizing the patterns and producing better results!
Can you give examples of what you mean by a user story? Does the AI need detailed specs to write good tests?