testing-patterns

name	testing-patterns
description	Testing patterns and principles. Unit, integration, mocking strategies.
when_to_use	When writing unit tests, integration tests, choosing testing frameworks, or implementing mocking strategies.

Testing Patterns

Principles for reliable test suites.

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1. Testing Pyramid

        /\          E2E (Few)
       /  \         Critical flows
      /----\
     /      \       Integration (Some)
    /--------\      API, DB queries
   /          \
  /------------\    Unit (Many)
                    Functions, classes

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2. AAA Pattern

Step	Purpose
Arrange	Set up test data
Act	Execute code under test
Assert	Verify outcome

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3. Test Type Selection

When to Use Each

Type	Best For	Speed
Unit	Pure functions, logic	Fast (<50ms)
Integration	API, DB, services	Medium
E2E	Critical user flows	Slow

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4. Unit Test Principles

Good Unit Tests

Principle	Meaning
Fast	< 100ms each
Isolated	No external deps
Repeatable	Same result always
Self-checking	No manual verification
Timely	Written with code

What to Unit Test

Test	Don't Test
Business logic	Framework code
Edge cases	Third-party libs
Error handling	Simple getters

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5. Integration Test Principles

What to Test

Area	Focus
API endpoints	Request/response
Database	Queries, transactions
External services	Contracts

Setup/Teardown

Phase	Action
Before All	Connect resources
Before Each	Reset state
After Each	Clean up
After All	Disconnect

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6. Mocking Principles

When to Mock

Mock	Don't Mock
External APIs	The code under test
Database (unit)	Simple dependencies
Time/random	Pure functions
Network	In-memory stores

Mock Types

Type	Use
Stub	Return fixed values
Spy	Track calls
Mock	Set expectations
Fake	Simplified implementation

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7. Test Organization

Naming

Pattern	Example
Should behavior	"should return error when..."
When condition	"when user not found..."
Given-when-then	"given X, when Y, then Z"

Grouping

Level	Use
describe	Group related tests
it/test	Individual case
beforeEach	Common setup

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8. Test Data

Strategies

Approach	Use
Factories	Generate test data
Fixtures	Predefined datasets
Builders	Fluent object creation

Principles

• Use realistic data
• Randomize non-essential values (faker)
• Share common fixtures
• Keep data minimal

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9. Best Practices

Practice	Why
One assert per test	Clear failure reason
Independent tests	No order dependency
Fast tests	Run frequently
Descriptive names	Self-documenting
Clean up	Avoid side effects

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10. Anti-Patterns

❌ Don't	✅ Do
Test implementation	Test behavior
Duplicate test code	Use factories
Complex test setup	Simplify or split
Ignore flaky tests	Fix root cause
Skip cleanup	Reset state

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Remember: Tests are documentation. If someone can't understand what the code does from the tests, rewrite them.