AI-Generated Tests
Unit tests, integration tests, edge cases, and test data.
5 min read
1 quiz questionsTesting is one of the best uses of AI in development. AI is excellent at identifying edge cases you might miss and generating comprehensive test suites quickly.
Unit Test Generator
Comprehensive unit tests covering happy paths, edges, and errors.
Write unit tests for this function: ```[LANGUAGE] [PASTE FUNCTION] ``` Test framework: [Jest/Vitest/pytest/etc.] Generate tests for: 1. Happy path (2-3 cases) 2. Edge cases (empty input, null/undefined, boundary values) 3. Error cases (invalid input, expected failures) 4. Type edge cases (wrong types if applicable) Follow AAA pattern (Arrange, Act, Assert). Use descriptive test names: "should [expected behavior] when [condition]". No mocking unless necessary — prefer real values.
AI-generated tests catch ~60-70% of bugs. They're excellent for coverage but won't replace thinking about your specific business logic edge cases.
Prompt Templates
Test Data Generator
Realistic test data with edge cases.
Generate realistic test data for [ENTITY TYPE]. Create 10 records as a JSON array. Include: valid records (7), edge cases (2: empty strings, max lengths, special characters), and one invalid record. Fields: [LIST FIELDS WITH TYPES]. Make names and values realistic, not "test1, test2".
Test Your Knowledge
Knowledge Check
1 / 1
What pattern should AI-generated tests follow?
Key Takeaways
- ✓AI excels at generating edge cases you might miss
- ✓Specify the test framework and patterns you want
- ✓Use AAA pattern for readable, maintainable tests
- ✓AI tests are a starting point — add business-logic-specific cases