Language-agnostic testing principles including TDD, test quality, coverage standards, and test design patterns. Use when writing tests, designing test strategies, or reviewing test quality.
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name: testing-principles description: Language-agnostic testing principles including TDD, test quality, coverage standards, and test design patterns. Use when writing tests, designing test strategies, or reviewing test quality.
Language-Agnostic Testing Principles
Core Testing Philosophy
- Tests are First-Class Code: Maintain test quality equal to production code
- Fast Feedback: Tests should run quickly and provide immediate feedback
- Reliability: Tests should be deterministic and reproducible
- Independence: Each test should run in isolation
Test-Driven Development (TDD)
The RED-GREEN-REFACTOR Cycle
Always follow this cycle:
-
RED: Write a failing test first
- Write the test before implementation
- Ensure the test fails for the right reason
- Verify test can actually fail
-
GREEN: Write minimal code to pass
- Implement just enough to make the test pass
- Don't optimize prematurely
- Focus on making it work
-
REFACTOR: Improve code structure
- Clean up implementation
- Eliminate duplication
- Improve naming and clarity
- Keep all tests passing
-
VERIFY: Ensure all tests still pass
- Run full test suite
- Check for regressions
- Validate refactoring didn't break anything
TDD Benefits
- Better design through testability requirements
- Comprehensive test coverage by default
- Living documentation of expected behavior
- Confidence to refactor
Quality Requirements
Coverage Standards
- Minimum 80% code coverage for production code
- Prioritize critical paths and business logic
- Don't sacrifice quality for coverage percentage
- Use coverage as a guide, not a goal
Test Characteristics
All tests must be:
- Independent: No dependencies between tests
- Reproducible: Same input always produces same output
- Fast: Complete test suite runs in reasonable time
- Self-checking: Clear pass/fail without manual verification
- Timely: Written close to the code they test
Test Types
Unit Tests
Purpose: Test individual components in isolation
Characteristics:
- Test single function, method, or class
- Fast execution (milliseconds)
- No external dependencies
- Mock external services
- Majority of your test suite
Example Scope:
✓ Test calculateTotal() function
✓ Test UserValidator class
✓ Test parseDate() utility
Integration Tests
Purpose: Test interactions between components
Characteristics:
- Test multiple components together
- May include database, file system, or APIs
- Slower than unit tests
- Verify contracts between modules
- Smaller portion of test suite
Example Scope:
✓ Test UserService with Database
✓ Test API endpoint with authentication
✓ Test file processing pipeline
End-to-End (E2E) Tests
Purpose: Test complete workflows from user perspective
Characteristics:
- Test entire application stack
- Simulate real user interactions
- Slowest test type
- Fewest in number
- Highest confidence level
Example Scope:
✓ Test user registration flow
✓ Test checkout process
✓ Test complete report generation
Test Pyramid
Follow the test pyramid structure:
/\ ← Few E2E Tests (High confidence, slow)
/ \
/ \ ← Some Integration Tests (Medium confidence, medium speed)
/ \
/________\ ← Many Unit Tests (Fast, foundational)
Test Design Principles
AAA Pattern (Arrange-Act-Assert)
Structure every test in three clear phases:
// Arrange: Setup test data and conditions
user = createTestUser()
validator = createValidator()
// Act: Execute the code under test
result = validator.validate(user)
// Assert: Verify expected outcome
assert(result.isValid == true)
Adaptation: Apply this structure using your language's idioms (methods, functions, procedures)
One Assertion Per Concept
- Test one behavior per test case
- Multiple assertions OK if testing single concept
- Split unrelated assertions into separate tests
Good:
test("validates user email format")
test("validates user age is positive")
test("validates required fields are present")
Bad:
test("validates user") // Tests everything at once
Descriptive Test Names
Test names should clearly describe:
- What is being tested
- Under what conditions
- What the expected outcome is
Recommended format: "should [expected behavior] when [condition]"
Examples:
test("should return error when email is invalid")
test("should calculate discount when user is premium")
test("should throw exception when file not found")
Adaptation: Follow your project's naming convention (camelCase, snake_case, describe/it blocks)
Test Independence
Isolation Requirements
- No shared state: Each test creates its own data
- No execution order dependency: Tests pass in any order
- Clean up after tests: Reset state, close connections
- Avoid global variables: Use local test data
Setup and Teardown
- Use setup hooks to prepare test environment
- Use teardown hooks to clean up resources
- Keep setup minimal and focused
- Ensure teardown runs even if test fails
Mocking and Test Doubles
When to Use Mocks
- Mock external dependencies: APIs, databases, file systems
- Mock slow operations: Network calls, heavy computations
- Mock unpredictable behavior: Random values, current time
- Mock unavailable services: Third-party services
Mocking Principles
- Mock at boundaries, not internally
- Keep mocks simple and focused
- Verify mock expectations when relevant
- Don't mock external libraries/frameworks you don't control (prefer adapters)
Types of Test Doubles
- Stub: Returns predetermined values
- Mock: Verifies it was called correctly
- Spy: Records information about calls
- Fake: Simplified working implementation
- Dummy: Passed but never used
Test Quality Practices
Keep Tests Active
- Fix or delete failing tests: Resolve failures immediately
- Remove commented-out tests: Fix them or delete entirely
- Keep tests running: Broken tests lose value quickly
- Maintain test suite: Refactor tests as needed
Test Code Quality
- Apply same standards as production code
- Use descriptive variable names
- Extract test helpers to reduce duplication
- Keep tests readable and maintainable
- Review test code thoroughly
Test Helpers and Utilities
- Create reusable test data builders
- Extract common setup into helper functions
- Build test utilities for complex scenarios
- Share helpers across test files appropriately
What to Test
Focus on Behavior
Test observable behavior, not implementation:
✓ Good: Test that function returns expected output ✓ Good: Test that correct API endpoint is called ✗ Bad: Test that internal variable was set ✗ Bad: Test order of private method calls
Test Public APIs
- Test through public interfaces
- Avoid testing private methods directly
- Test return values, outputs, exceptions
- Test side effects (database, files, logs)
Test Edge Cases
Always test:
- Boundary conditions: Min/max values, empty collections
- Error cases: Invalid input, null values, missing data
- Edge cases: Special characters, extreme values
- Happy path: Normal, expected usage
Test Quality Criteria
These criteria ensure reliable, maintainable tests.
Literal Expected Values
- Use hardcoded literal values in assertions
- Calculate expected values independently from the implementation
- If the implementation has a bug, the test catches it through independent verification
- If expected value equals mock return value unchanged, the test verifies nothing (no transformation occurred)
Result-Based Verification
- Verify final results and observable outcomes
- Assert on return values, output data, or system state changes
- For mock verification, check that correct arguments were passed
Meaningful Assertions
- Every test must include at least one assertion
- Assertions must validate observable behavior
- A test without assertions always passes and provides no value
Appropriate Mock Scope
- Mock direct external I/O dependencies: databases, HTTP clients, file systems
- Use real implementations for internal utilities and business logic
- Over-mocking reduces test value by verifying wiring instead of behavior
Boundary Value Testing
Test at boundaries of valid input ranges:
- Minimum valid value
- Maximum valid value
- Just below minimum (invalid)
- Just above maximum (invalid)
- Empty input (where applicable)
Test Independence Verification
Each test must:
- Create its own test data
- Not depend on execution order
- Clean up its own state
- Pass when run in isolation
Verification Requirements
Before Commit
- ✓ All tests pass
- ✓ No tests skipped or commented
- ✓ No debug code left in tests
- ✓ Test coverage meets standards
- ✓ Tests run in reasonable time
Zero Tolerance Policy
- Zero failing tests: Fix immediately
- Zero skipped tests: Delete or fix
- Zero flaky tests: Make deterministic
- Zero slow tests: Optimize or split
Test Organization
File Structure
- Mirror production structure: Tests follow code organization
- Clear naming conventions: Follow project's test file patterns
- Examples:
UserService.test.*,user_service_test.*,test_user_service.*,UserServiceTests.*
- Examples:
- Logical grouping: Group related tests together
- Separate test types: Unit, integration, e2e in separate directories
Test Suite Organization
tests/
├── unit/ # Fast, isolated unit tests
├── integration/ # Integration tests
├── e2e/ # End-to-end tests
├── fixtures/ # Test data and fixtures
└── helpers/ # Shared test utilities
Performance Considerations
Test Speed
- Unit tests: < 100ms each
- Integration tests: < 1s each
- Full suite: Should run frequently (< 10 minutes)
Optimization Strategies
- Run tests in parallel when possible
- Use in-memory databases for tests
- Mock expensive operations
- Split slow test suites
- Profile and optimize slow tests
Continuous Integration
CI/CD Requirements
- Run full test suite on every commit
- Block merges if tests fail
- Run tests in isolated environments
- Test on target platforms/versions
Test Reports
- Generate coverage reports
- Track test execution time
- Identify flaky tests
- Monitor test trends
Common Anti-Patterns to Avoid
Test Smells
- ✗ Tests that test nothing (always pass)
- ✗ Tests that depend on execution order
- ✗ Tests that depend on external state
- ✗ Tests with complex logic (tests shouldn't need tests)
- ✗ Testing implementation details
- ✗ Excessive mocking (mocking everything)
- ✗ Test code duplication
Flaky Tests
Eliminate tests that fail intermittently:
- Remove timing dependencies
- Avoid random data in tests
- Ensure proper cleanup
- Fix race conditions
- Make tests deterministic
Regression Testing
Prevent Regressions
- Add test for every bug fix
- Maintain comprehensive test suite
- Run full suite regularly
- Don't delete tests without good reason
Legacy Code
- Add characterization tests before refactoring
- Test existing behavior first
- Gradually improve coverage
- Refactor with confidence
Testing Best Practices by Language Paradigm
Type System Utilization
For languages with static type systems:
- Leverage compile-time verification for correctness
- Focus tests on business logic and runtime behavior
- Use language's type system to prevent invalid states
For languages with dynamic typing:
- Add comprehensive runtime validation tests
- Explicitly test data contract validation
- Consider property-based testing for broader coverage
Programming Paradigm Considerations
Functional approach:
- Test pure functions thoroughly (deterministic, no side effects)
- Test side effects at system boundaries
- Leverage property-based testing for invariants
Object-oriented approach:
- Test behavior through public interfaces
- Mock dependencies via abstraction layers
- Test polymorphic behavior carefully
Common principle: Adapt testing strategy to leverage language strengths while ensuring comprehensive coverage
Documentation and Communication
Tests as Documentation
- Tests document expected behavior
- Use clear, descriptive test names
- Include examples of usage
- Show edge cases and error handling
Test Failure Messages
- Provide clear, actionable error messages
- Include actual vs expected values
- Add context about what was being tested
- Make debugging easier
Continuous Improvement
Review and Refactor Tests
- Refactor tests as you refactor code
- Remove obsolete tests
- Improve test clarity
- Update tests for new patterns
Learn from Failures
- Analyze test failures thoroughly
- Add tests for discovered edge cases
- Improve test coverage where gaps found
- Share learnings with team
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