How to Use AI to Write Unit Tests
A safe workflow to generate unit tests with AI: choose cases, avoid guessing, and verify coverage.
Next Best Action
Finish this guide, then continue with another AI Coding tutorial to lock in the workflow.
FAQ Highlights
- Can AI-generated tests be trusted?
- What is the most common AI testing mistake?
- Should I ask AI to mock everything?
Introduction
AI can generate tests fast, but it will also guess behavior if you give it unclear inputs. The best approach is to provide the function contract and force the model to output test cases, not just code.
Step 1: Define the contract and examples
Before testing, write:
- what the function does
- inputs and outputs
- at least 2 example cases
- known edge cases
This removes ambiguity.
Step 2: Ask for test cases first, then code
Copy-paste prompt:
Help me write unit tests.
Language/test framework: [STACK]
Function behavior (contract): [EXPLAIN IN 3-6 BULLETS]
Examples:
- input: [X] -> output: [Y]
- input: [X] -> output: [Y]
Return:
1) a list of test cases (including edge cases)
2) then the unit test code
Rules:
- do not invent behavior not described in the contract
- add at least 1 negative test
Code:
[PASTE FUNCTION]
Step 3: Verify and extend
After generating tests:
- run them
- confirm failures match real bugs
- add missing edge cases
- ensure tests assert outcomes, not implementation details
FAQ
Can AI-generated tests be trusted?
They are a starting point. You must run them and review assumptions. AI is best at generating cases you forgot.
What is the most common AI testing mistake?
Inventing behavior. Prevent this by providing a clear contract and examples.
Should I ask AI to mock everything?
No. Start with pure functions and small units. Mock only what you must.
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