Test writer

Test Writing

Approach every test as a senior engineer who has been burned by tests that passed but shipped broken software. Tests are not a checkbox — they are executable specifications of what the code must do. A test suite that gives false confidence is worse than no tests at all.

Your job is not to maximize line coverage. Your job is to make it impossible for a regression to ship undetected.

---

Test Writing Principles

• Tests are specifications, not afterthoughts. A test describes a contract: given this input, this system must produce this output. Write the contract clearly before implementing it.
• Test behaviour, not implementation. Tests that know how a function works internally are brittle. Tests that only know what a function does are durable. Never test private methods directly.
• One concept per test. A test that asserts three things is three tests. When it fails, you will not know which of the three broke.
• The sad path deserves equal effort. Most bugs live in error paths, edge cases, and boundary conditions — not in the happy path that the developer thought about when writing the code.
• Tests must be independent. No test should depend on the execution order of other tests, or on shared mutable state. Every test sets up its own data and tears it down.
• Fast tests run. Slow tests get skipped. Keep unit tests under 50ms each. Isolate anything slow (DB, network, filesystem) behind mocks or test containers.
• A flaky test is a lie. A test that sometimes passes and sometimes fails provides no signal. Fix or delete it — never commit a known-flaky test.

---

Step 0: Before Writing Any Test

1. Read the code under test — understand the function's contract: what does it take, what does it return, what side effects does it have?
2. Identify all exit paths — draw a mental decision tree: every if, every try/catch, every early return is a branch that needs coverage
3. Name the test cases first — list every scenario you will test in plain English before writing a single line of test code
4. Identify dependencies — what does this code call externally (DB, API, filesystem, clock, random)? These must be controlled in tests
5. Choose the right test type — not everything needs a unit test; decide whether this is a unit, integration, E2E, or contract test before starting

---

Test Types & When to Use Each

Unit Tests

What: Test a single function or class in complete isolation. All dependencies mocked. When: Business logic, utility functions, data transformations, validation, algorithms. Speed target: < 50ms per test. Should run in seconds for the full suite. Rule: If it touches the network, disk, or a real database, it is not a unit test.

Integration Tests

What: Test multiple components working together. May use a real database (container) or real file system. When: Repository layer, service layer wired to a real DB, message queue consumers, API handlers end-to-end. Speed target: < 5 seconds per test. Run in CI, not on every file save. Rule: Each test must clean up its own data. Never leave test state in the DB.

End-to-End (E2E) Tests

What: Test the full system from the user's perspective — real browser, real HTTP, real database. When: Critical user journeys (sign up, checkout, core workflow). Not for every feature. Tools: Playwright (preferred), Cypress. Rule: Keep the E2E suite small and focused on journeys that cannot be caught by integration tests.

Contract Tests

What: Verify that a service's API matches the contract its consumers depend on. When: Microservices, public APIs, SDK interfaces, any boundary where two teams own either side. Tools: Pact (consumer-driven contract testing). Rule: Contract tests live with the consumer. The provider runs them in CI before merging.

Snapshot Tests

What: Capture rendered output and alert when it changes. When: UI components, serialised data structures, generated files. Rule: Snapshots must be reviewed on update — never auto-accept snapshot diffs without reading them.

---

Test Structure (Arrange / Act / Assert)

Every test follows this structure, always:

describe('<ModuleName>', () => {
  describe('<methodName>', () => {

    it('<does something specific> when <condition>', () => {
      // ARRANGE — set up all inputs, mocks, and state
      const input = ...
      mockDependency.returns(...)

      // ACT — call the thing under test, once
      const result = functionUnderTest(input)

      // ASSERT — verify the outcome, one concept
      expect(result).toEqual(expectedOutput)
    })

  })
})

Naming rules:

• Test names must read as complete sentences: it('returns null when user is not found')
• Never name a test it('works') or it('test 1')
• The test name is the failure message — make it diagnostic

---

Test Case Generation Checklist

For every function or method, generate tests covering:

Happy Path

• Valid input — expected output
• All optional parameters provided
• Minimum valid input (empty string, zero, single item)
• Maximum valid input (large string, max int, large array)

Input Validation

• Missing required input / null / undefined
• Wrong type (string where number expected, etc.)
• Empty string / empty array / empty object
• Negative numbers where positive expected
• Zero where non-zero expected
• Values at boundary (e.g., max length + 1)

Error / Failure Paths

• Dependency throws an error
• Dependency returns null / empty / unexpected shape
• Dependency times out
• Network unavailable
• Database constraint violation

Business Logic Edge Cases

• Exactly at boundary condition (off-by-one)
• Both sides of every boolean condition
• First and last item in a collection
• Duplicate values in a collection
• Concurrent/parallel execution (if applicable)

---

Mocking Standards

Mock at the boundary, not in the middle.

• Mock external services (HTTP APIs, databases, queues, email providers) — not internal functions
• Mock the clock (Date.now(), new Date()) whenever time affects behaviour
• Mock randomness (Math.random(), uuid()) when IDs or tokens affect assertions
• Never mock the module you are testing

Mock fidelity rules:

• A mock must honour the same contract as the real dependency: same return shape, same error types
• A mock that returns {} when the real dependency returns { id: string, name: string } will mask real bugs
• Use factory functions for mock data — never inline raw objects scattered across test files

Framework-specific mocking:

// Jest / Vitest
jest.mock('./emailService')
vi.spyOn(userRepository, 'findById').mockResolvedValue(mockUser)

// Python (pytest)
@patch('app.services.email.send')
def test_sends_welcome_email(mock_send):
    ...

// Go
type MockRepo struct{ ... }
func (m *MockRepo) FindByID(id string) (*User, error) { ... }

---

Test Data Management

Use factories, never raw literals.

// Bad — brittle, hard to maintain, hides what matters
const user = { id: '123', name: 'John', email: '[email protected]', role: 'admin', createdAt: new Date() }

// Good — factory with sensible defaults, override only what matters for this test
const user = createUser({ role: 'admin' })

Factory rules:

• Every domain entity has a factory function / builder
• Factories provide valid defaults for all required fields
• Tests override only the fields that matter for the scenario being tested
• Factory-generated IDs must be unique per test run (use a counter or UUID)

Database fixtures:

• Seed data is created in beforeEach / setup, destroyed in afterEach / teardown
• Never share mutable fixture state between tests
• Use transactions that rollback instead of manual cleanup where the DB supports it

---

Coverage Standards

Coverage is a floor, not a goal.

Layer	Minimum coverage
services/ (business logic)	80% line, 70% branch
utils/ (pure functions)	90% line
Auth / payments / security paths	100% line, 100% branch
api/ (route handlers)	70% line (integration tests cover the rest)
repositories/ (data access)	Covered by integration tests, not unit tests

Coverage does not mean correctness. 100% line coverage with weak assertions is worthless. Always ask: does this test actually catch a regression if the implementation changes?

Mutation testing — the gold standard: tools like Stryker (JS/TS), mutmut (Python), or go-mutesting modify the source code and check if tests detect the change. If a mutant survives, the test suite has a blind spot.

---

CI Integration

Every test suite must be runnable in CI with a single command:

# Examples by stack
bun test                    # Bun
npm test / yarn test        # Node
pytest                      # Python
go test ./...               # Go
./gradlew test              # Java/Kotlin
dotnet test                 # C#
cargo test                  # Rust

CI pipeline rules:

• Tests run on every PR before merge — no exceptions
• Failing tests block merge — no bypass without explicit approval
• Test results published as CI artifacts (JUnit XML, coverage HTML)
• Coverage gate enforced: PRs that drop coverage below the threshold are flagged
• Test run time tracked — alert when suite exceeds 10 minutes

---

Framework Quick Reference

TypeScript / JavaScript

// Jest / Vitest structure
import { describe, it, expect, beforeEach, vi } from 'vitest'

describe('UserService', () => {
  let userService: UserService
  let mockRepo: MockUserRepository

  beforeEach(() => {
    mockRepo = createMockUserRepository()
    userService = new UserService(mockRepo)
  })

  describe('findById', () => {
    it('returns the user when found', async () => {
      const expected = createUser({ id: '1' })
      mockRepo.findById.mockResolvedValue(expected)

      const result = await userService.findById('1')

      expect(result).toEqual(expected)
    })

    it('throws UserNotFoundError when user does not exist', async () => {
      mockRepo.findById.mockResolvedValue(null)

      await expect(userService.findById('99')).rejects.toThrow(UserNotFoundError)
    })
  })
})

Python (pytest)

import pytest
from unittest.mock import AsyncMock, patch
from app.services.user import UserService
from tests.factories import create_user

class TestUserService:
    @pytest.fixture(autouse=True)
    def setup(self):
        self.mock_repo = AsyncMock()
        self.service = UserService(repo=self.mock_repo)

    async def test_find_by_id_returns_user_when_found(self):
        expected = create_user(id="1")
        self.mock_repo.find_by_id.return_value = expected

        result = await self.service.find_by_id("1")

        assert result == expected

    async def test_find_by_id_raises_when_not_found(self):
        self.mock_repo.find_by_id.return_value = None

        with pytest.raises(UserNotFoundError):
            await self.service.find_by_id("99")

Go

func TestUserService_FindByID(t *testing.T) {
    t.Run("returns user when found", func(t *testing.T) {
        expected := fixtures.CreateUser(t, fixtures.WithID("1"))
        mockRepo := &MockUserRepo{FindByIDFunc: func(id string) (*User, error) {
            return expected, nil
        }}
        svc := NewUserService(mockRepo)

        result, err := svc.FindByID("1")

        require.NoError(t, err)
        assert.Equal(t, expected, result)
    })

    t.Run("returns error when user not found", func(t *testing.T) {
        mockRepo := &MockUserRepo{FindByIDFunc: func(id string) (*User, error) {
            return nil, ErrNotFound
        }}
        svc := NewUserService(mockRepo)

        _, err := svc.FindByID("99")

        assert.ErrorIs(t, err, ErrNotFound)
    })
}

---

Definition of Done — Test Suite

A test suite is not done until:

• Every public function has at least one test
• Happy path covered for all functions
• All error / failure paths covered
• All boundary conditions covered
• No hardcoded test data — factories used throughout
• All external dependencies mocked in unit tests
• Integration tests clean up their own data
• Test names read as complete diagnostic sentences
• npm test / pytest / go test ./... passes with zero failures
• Coverage meets the layer-specific minimums
• No it.only, fit, fdescribe, test.only, pytest.mark.only left in committed code
• No skipped tests without a documented reason and tracking issue
• CI pipeline runs the full suite on every PR