Why Testing Matters in JavaScript & TypeScript

JavaScript and TypeScript are dynamic, loosely-typed languages that require robust testing to maintain reliability. Without proper tests, issues such as runtime errors, unintended side effects, and regressions can easily slip into production.

Benefits of Testing

  • Reduces Bugs: Automated tests catch errors early.
  • Improves Maintainability: Ensures that code changes don’t break existing functionality.
  • Enables Confident Refactoring: Provides safety nets for modifying code.

Common Misconceptions

  • "Tests slow down development": Proper tests save time in the long run by reducing debugging efforts.
  • "100% coverage guarantees bug-free code": Coverage is important, but meaningful test cases matter more.
  • "Mock everything": Over-mocking can result in tests that do not reflect real-world behavior.

Common Testing Mistakes and How to Avoid Them

Mistake #1: Not Testing Async Code Properly

The Problem

  • Failing to handle asynchronous operations correctly.
  • Tests passing even when async code fails due to improper assertions.

Bad Example

it("should return user data when fetchData is called", () => {
  const data = fetchData(); // Missing await
  
  expect(data.name).toBe("John"); // This assertion will always pass
});

Solution

  • Always use await with async functions.
  • Use Jest’s expect.assertions() to ensure assertions execute.

Corrected Example

it("should correctly fetch user data when fetchData is called", async () => {
  expect.assertions(1);
  
  const data = await fetchData();
  
  expect(data.name).toBe("John");
});

Mistake #2: Over-Mocking Dependencies

The Problem

  • Mocking everything instead of testing actual integrations.
  • Risk of testing the mock behavior rather than real functionality.

Solution

  • Use real data in integration tests when possible.
  • Prefer spies over full mocks for simple functions.

Example Using Jest Mocks

jest.mock("../api", () => ({
  fetchData: jest.fn(() => Promise.resolve({ name: "John" })),
}));

Mistake #3: Not Cleaning Up After Tests

The Problem

  • State pollution between tests, leading to flaky tests.
  • Memory leaks in Jest or Mocha test suites.

Solution

  • Use Jest’s beforeEach() and afterEach() to reset mocks.
  • Use fake timers for time-sensitive tests.

Example

beforeEach(() => {
  jest.clearAllMocks();
});

Mistake #4: Writing Slow, Bloated Tests

The Problem

  • Over-reliance on full-stack tests instead of unit tests.
  • Tests interacting with real databases instead of in-memory solutions.

Solution

  • Use in-memory databases like SQLite for Jest tests.
  • Favor unit tests over full integration tests for simple logic.

Example

import { createConnection } from "typeorm";

let connection;

beforeAll(async () => {
  connection = await createConnection({
    type: "sqlite",
    database: ":memory:",
    entities: [User],
    synchronize: true,
  });
});

afterAll(async () => {
  await connection.close();
});

Mistake #5: Poorly Written Test Names and Assertions

The Problem

  • Vague or generic test descriptions.
  • Assertions that don't fully check expected outcomes.

Bad Example

it("should work", () => {
  expect(1).toBe(1);
});

Good Example

it("should correctly sum up product prices in calculateTotalPrice", () => {
  const result = calculateTotalPrice([{ price: 10 }, { price: 20 }]);
  expect(result).toBe(30);
});

Mistake #6: Not Testing Edge Cases

The Problem

  • Only testing the “happy path.”
  • Missing runtime errors such as null or undefined handling.

Solution

  • Use property-based testing to test random inputs.
  • Write negative test cases for edge scenarios.

Example

it("should return 0 when calculateTotalPrice is given an empty array", () => {
  expect(calculateTotalPrice([])).toBe(0);
});

it("should throw an error when calculateTotalPrice receives null input", () => {
  expect(() => calculateTotalPrice(null)).toThrow();
});

Mistake #7: Not Using TypeScript for Better Test Safety

The Problem

  • Writing tests in JavaScript without leveraging TypeScript’s type safety.
  • Catching type errors only at runtime instead of during compilation.

Solution

  • Use TypeScript in test files (.test.ts).
  • Enable strict mode in tsconfig.json.

Example

it("should return user data from UserService.getUser", async () => {
  const user: User = await UserService.getUser(1);
  
  expect(user).toMatchObject({ id: 1, name: expect.any(String) });
});

Best Practices for High-Quality Tests in JavaScript & TypeScript

✅ Use async/await properly in tests
✅ Prefer behavioral testing over implementation-based tests
✅ Clean up mock states and database connections between tests
✅ Keep tests small and fast to encourage frequent execution
✅ Ensure test names are descriptive and meaningful
✅ Use TypeScript for type safety in tests
✅ Maintain a balance between unit tests and integration tests

Conclusion and Takeaways

  • Proper testing in JavaScript and TypeScript prevents common pitfalls like flaky tests and untested edge cases.
  • Avoid mistakes like over-mocking, not cleaning up, and writing slow tests.
  • Use the right tools (Jest, Mocha, Cypress) and meaningful test cases.
  • Testing should increase confidence, not just code coverage.