Unit Test
Generate comprehensive unit test cases for Jest, pytest, JUnit, XCTest, and Vitest with edge cases, mocks, and error handling in 60 seconds.
Overview
Generate comprehensive unit test suites for JavaScript (Jest, Vitest), Python (pytest), Java (JUnit), Swift (XCTest), and other frameworks. Produces complete test files with setup/teardown, happy path tests, edge case coverage, error handling, and mock requirements.
Takes 3 minutes to set up, generates tests in under 60 seconds.
Use Cases
- Write test suites for REST API endpoints during sprint planning
- Generate pytest test cases for data validation functions in Python services
- Create XCTest suites for Swift UI components before pull request reviews
- Build JUnit tests for Java microservice business logic
- Generate Jest test files for React component state management
- Add test coverage for legacy code before refactoring production systems
Template
Generate unit tests for:
Function/Method: {{functionName}}
Language/Framework: {{framework}}
Function description:
{{description}}
Edge cases to test:
{{edgeCases}}
Include:
- Test setup and teardown
- Happy path tests
- Edge case tests
- Error handling tests
- Mock/stub requirements
Test coverage goal: {{coverage}}%
Properties
- functionName: Single-line Text
- framework: Single Selection (default:
Jest)- Options: Jest (JavaScript), Vitest (JavaScript), pytest (Python), JUnit (Java), XCTest (Swift), and 2 more
- description: Multi-line Text
- edgeCases (optional): Multi-line Text
- coverage: Single Selection (default:
80)- Options: 70%, 80%, 90%, 100%
Benefits
- Save 15-30 minutes per function - Generate complete test suites instead of writing boilerplate test code manually
- Catch edge cases before production - Automatically includes boundary conditions, null checks, and invalid input handling
- Maintain consistent test structure - Every test suite follows framework best practices with proper setup and teardown
- Speed up code reviews - Tests written before implementation help reviewers understand function behavior
- Reduce debugging time - Comprehensive error handling tests catch issues during development, not production
- Hit coverage targets faster - Generate 70-100% test coverage without manually calculating which paths need tests
Example Output
Input values:
- Function:
calculateDiscount - Framework: Jest (JavaScript)
- Description: Calculates discounted price based on percentage
- Edge cases: Zero discount, 100% discount, negative values, non-numeric inputs
- Coverage: 80%
Generated test suite structure:
// Complete Jest test suite with 30+ test cases
describe('calculateDiscount', () => {
// Happy Path Tests (3 cases)
- Standard percentages (10%, 25%, 50%)
- Decimal prices and discount percentages
// Edge Cases (5 cases)
- Zero discount returns original price
- 100% discount returns zero
- Zero price handling
- Very small and large price values
// Error Handling - Negative Values (3 cases)
- Negative price throws error
- Negative discount throws error
- Both negative values
// Error Handling - Non-numeric Inputs (8 cases)
- String, null, undefined inputs
- Objects, arrays, booleans, NaN
// Invalid Discount Percentages (2 cases)
- Discount over 100%
- Very large percentage values
// Boundary Values (3 cases)
- 0%, 100%, 99.99% discounts
});
The complete output includes beforeEach/afterEach setup, specific assertions, and mock requirements where needed.
Common Mistakes to Avoid
Testing implementation details instead of behavior - Tests should verify what the function does, not how it does it. If you refactor the internal logic, tests shouldn’t break unless behavior changes.
Missing edge cases - The most common bugs hide in boundary conditions. Always test zero, null, undefined, negative values, and maximum/minimum limits for your data type.
Writing brittle tests - Hard-coding expected values makes tests fragile. Use test data that clearly shows the relationship between input and output.
Skipping error handling tests - Production code fails in unexpected ways. Test what happens when the database is down, the API times out, or users send malformed data.
Ignoring async behavior - For async functions, remember to await promises or use done() callbacks. Forgotten awaits cause tests to pass when they should fail.
Not mocking external dependencies - Tests should run fast and not depend on databases, APIs, or file systems. Mock everything outside your function’s control.
Aiming for 100% coverage blindly - High coverage doesn’t mean good tests. Focus on testing critical paths and edge cases rather than hitting arbitrary coverage numbers.
Frequently Used With
Generate comprehensive test coverage by combining with related templates:
- Code Review - Review implementation before writing tests to catch design issues early
- Bug Report - Convert bug reports into regression test cases
- Refactoring Plan - Add test coverage before refactoring legacy code
- API Documentation - Document endpoints while writing integration tests