Stop Writing Fragile Tests: Your TypeScript Unit Testing Game Plan

Writing unit tests shouldn't feel like navigating a minefield. Yet most TypeScript developers find themselves wrestling with flaky tests, brittle snapshots, and test suites that take forever to run. Sound familiar?

The Real Problem with Most Test Suites

Here's what's actually happening in most codebases:

Tests break when you refactor - they're testing implementation details instead of behavior
Slow feedback loops - waiting 5+ minutes for tests kills your flow state
Mock hell - over-mocking makes tests harder to understand than the code they're testing
Coverage theater - high percentages that don't actually catch bugs
CI nightmares - flaky tests that randomly fail and block deployments

These aren't just minor annoyances. They're productivity killers that make developers avoid writing tests altogether.

A Battle-Tested Approach to TypeScript Testing

These Cursor Rules transform your testing workflow by focusing on what actually matters: fast, reliable tests that catch real bugs and don't break when you refactor.

Instead of generic testing advice, you get opinionated rules that solve specific TypeScript testing pain points:

// Before: Testing implementation details
it('should call userService.getUser with correct ID', () => {
  const spy = jest.spyOn(userService, 'getUser');
  component.loadUser(123);
  expect(spy).toHaveBeenCalledWith(123);
});

// After: Testing behavior
it('displays user name when user loads successfully', async () => {
  const user = { id: 123, name: 'John Doe' };
  jest.spyOn(userService, 'getUser').mockResolvedValue(user);
  
  await component.loadUser(123);
  
  expect(component.displayName).toBe('John Doe');
});

Key Benefits That Actually Matter

Sub-10-Second Local Test Runs

Configured Jest settings and parallel execution patterns that keep your entire test suite under 10 seconds locally. No more context-switching while waiting for results.

Refactor-Proof Tests

Focus on testing behavior, not implementation. Your tests survive code restructuring because they're asserting what users care about, not how you implemented it.

Comprehensive Error Coverage

Systematic approach to normal, boundary, error, and edge cases. No more "but it works on my machine" bugs slipping through.

Zero-Config CI Integration

GitHub Actions setup that fails fast, caches dependencies, and provides meaningful coverage reports without the usual CI/CD headaches.

Real Developer Workflows These Rules Improve

TDD Without the Pain

// Write the failing test first
describe('validateEmail()', () => {
  it('returns null when email is valid', () => {
    expect(validateEmail('[email protected]')).toBe(null);
  });
  
  it('throws DomainError when email is invalid', () => {
    expect(() => validateEmail('invalid')).toThrow(DomainError);
  });
});

// Then write minimal code to pass
export function validateEmail(email: string): null {
  if (!email.includes('@')) {
    throw new DomainError('Invalid email format');
  }
  return null;
}

Smart Mocking Strategy

Instead of mocking everything, these rules teach you what to mock and when:

// Mock boundaries, not your own code
beforeEach(() => {
  jest.useFakeTimers();
  jest.spyOn(Date, 'now').mockReturnValue(1609459200000); // Fixed timestamp
});

// Use MSW for HTTP instead of complex fetch mocks
import { rest } from 'msw';
import { server } from '../test-utils/server';

server.use(
  rest.get('/api/users/:id', (req, res, ctx) => {
    return res(ctx.json({ id: 1, name: 'Test User' }));
  })
);

Coverage That Actually Catches Bugs

Focus on critical paths with meaningful thresholds:

// jest.config.ts
coverageThreshold: {
  global: {
    branches: 80,    // Catches missing error handling
    functions: 85,   // Ensures public API coverage
    lines: 85,      // Reasonable without gaming the system
    statements: 85  // Catches dead code
  }
}

Implementation Guide

Step 1: Install the Foundation

npm install -D jest ts-jest @types/jest msw

Step 2: Configure Jest for Speed

Create jest.config.ts:

export default {
  preset: 'ts-jest',
  testEnvironment: 'node',
  collectCoverage: true,
  coverageDirectory: 'coverage',
  coverageThreshold: { 
    global: { branches: 80, functions: 85, lines: 85, statements: 85 } 
  },
  moduleNameMapper: { '^@/(.*)$': '<rootDir>/src/$1' },
  resetMocks: true,
  restoreMocks: true,
  clearMocks: true,
};

Step 3: Set Up Test Structure

Place test files next to source code:

src/
  user/
    user.service.ts
    user.service.spec.ts
    user.controller.ts
    user.controller.spec.ts

Step 4: Create Your First Behavior-Driven Test

import { UserService } from './user.service';

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

  beforeEach(() => {
    userService = new UserService();
  });

  it('returns null when user is unauthenticated', () => {
    const result = userService.getCurrentUser(null);
    expect(result).toBe(null);
  });

  it('throws DomainError when user ID is invalid', () => {
    expect(() => userService.getUser(-1)).toThrow(DomainError);
  });
});

Step 5: Add CI Integration

Create .github/workflows/test.yml:

name: test
on: [push, pull_request]
jobs:
  unit:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: pnpm/action-setup@v2
        with: { version: 8 }
      - run: pnpm install --frozen-lockfile
      - run: pnpm test -- --ci
      - uses: codecov/codecov-action@v3

Results & Impact You'll See Immediately

Week 1: Faster Feedback

Your test suite runs in under 10 seconds locally. You'll run tests more frequently because there's no friction.

Week 2: Confident Refactoring

You'll refactor code without fear because your tests are asserting behavior, not implementation details.

Month 1: Fewer Production Bugs

Systematic error case coverage catches edge cases before they reach production.

Month 3: Team Adoption

Other developers start asking about your testing approach because your code has fewer bugs and your tests actually help during code reviews.

The difference between these rules and typical testing advice? These are battle-tested patterns from teams shipping production TypeScript applications, not theoretical best practices.

Stop writing tests that break when you refactor. Start building a test suite that actually helps you ship better code faster.

Robust Unit-Testing Rules for TypeScript/Jest