Table of Contents

Section 0: The Golden Rule

A single advice that inspires all the others (1 special bullet)

Section 1: The Test Anatomy

The foundation - structuring clean tests (12 bullets)

Section 2: Backend

Writing backend and Microservices tests efficiently (13 bullets)

Section 3: Frontend

Writing tests for web UI including component and E2E tests (11 bullets)

Section 4: Measuring Tests Effectiveness

Watching the watchman - measuring test quality (4 bullets)

Section 5: Continuous Integration

Guidelines for CI in the JS world (9 bullets)

Section 0️⃣: The Golden Rule

⚪️ 0 The Golden Rule: Design for lean testing

:white_check_mark: Do: Testing code is not production-code - Design it to be short, dead-simple, flat, and delightful to work with. One should look at a test and get the intent instantly.

See, our minds are already occupied with our main job - the production code. There is no 'headspace' for additional complexity. Should we try to squeeze yet another sus-system into our poor brain it will slow the team down which works against the reason we do testing. Practically this is where many teams just abandon testing.

The tests are an opportunity for something else - a friendly assistant, co-pilot, that delivers great value for a small investment. Science tells us that we have two brain systems: system 1 is used for effortless activities like driving a car on an empty road and system 2 is meant for complex and conscious operations like solving a math equation. Design your test for system 1, when looking at test code it should feel as easy as modifying an HTML document and not like solving 2X(17 × 24).

This can be achieved by selectively cherry-picking techniques, tools, and test targets that are cost-effective and provide great ROI. Test only as much as needed, and strive to keep it nimble, sometimes it's even worth dropping some tests and trading reliability for agility and simplicity.

Most of the advice below are derivatives of this principle.

Ready to start?

Section 1: The Test Anatomy

⚪ ️ 1.1 Include 3 parts in each test name

:white_check_mark: Do: A test report should tell whether the current application revision satisfies the requirements for the people who are not necessarily familiar with the code: the tester, the DevOps engineer who is deploying and the future you two years from now. This can be achieved best if the tests speak at the requirements level and include 3 parts:

(1) What is being tested? For example, the ProductsService.addNewProduct method

(2) Under what circumstances and scenario? For example, no price is passed to the method

(3) What is the expected result? For example, the new product is not approved

❌ Otherwise: A deployment just failed, a test named “Add product” failed. Does this tell you what exactly is malfunctioning?

👇 Note: Each bullet has code examples and sometime also an image illustration. Click to expand

:clap: Doing It Right Example: A test name that constitutes 3 parts

//1. unit under test
describe('Products Service', function() {
  describe('Add new product', function() {
    //2. scenario and 3. expectation
    it('When no price is specified, then the product status is pending approval', ()=> {
      const newProduct = new ProductService().add(...);
      expect(newProduct.status).to.equal('pendingApproval');
    });
  });
});

:clap: Doing It Right Example: A test name that constitutes 3 parts

⚪ ️ 1.2 Structure tests by the AAA pattern

:white_check_mark: Do: Structure your tests with 3 well-separated sections Arrange, Act & Assert (AAA). Following this structure guarantees that the reader spends no brain-CPU on understanding the test plan:

1st A - Arrange: All the setup code to bring the system to the scenario the test aims to simulate. This might include instantiating the unit under test constructor, adding DB records, mocking/stubbing on objects, and any other preparation code

2nd A - Act: Execute the unit under test. Usually 1 line of code

3rd A - Assert: Ensure that the received value satisfies the expectation. Usually 1 line of code

❌ Otherwise: Not only do you spend hours understanding the main code but what should have been the simplest part of the day (testing) stretches your brain

:clap: Doing It Right Example: A test structured with the AAA pattern

describe("Customer classifier", () => {
  test("When customer spent more than 500$, should be classified as premium", () => {
    //Arrange
    const customerToClassify = { spent: 505, joined: new Date(), id: 1 };
    const DBStub = sinon.stub(dataAccess, "getCustomer").reply({ id: 1, classification: "regular" });

    //Act
    const receivedClassification = customerClassifier.classifyCustomer(customerToClassify);

    //Assert
    expect(receivedClassification).toMatch("premium");
  });
});

:thumbsdown: Anti-Pattern Example: No separation, one bulk, harder to interpret

test("Should be classified as premium", () => {
  const customerToClassify = { spent: 505, joined: new Date(), id: 1 };
  const DBStub = sinon.stub(dataAccess, "getCustomer").reply({ id: 1, classification: "regular" });
  const receivedClassification = customerClassifier.classifyCustomer(customerToClassify);
  expect(receivedClassification).toMatch("premium");
});

⚪ ️1.3 Describe expectations in a product language: use BDD-style assertions

:white_check_mark: Do: Coding your tests in a declarative-style allows the reader to get the grab instantly without spending even a single brain-CPU cycle. When you write imperative code that is packed with conditional logic, the reader is forced to exert more brain-CPU cycles. In that case, code the expectation in a human-like language, declarative BDD style using expect or should and not using custom code. If Chai & Jest doesn't include the desired assertion and it’s highly repeatable, consider extending Jest matcher (Jest) or writing a custom Chai plugin

❌ Otherwise: The team will write less tests and decorate the annoying ones with .skip()

:thumbsdown: Anti-Pattern Example: The reader must skim through not so short, and imperative code just to get the test story

test("When asking for an admin, ensure only ordered admins in results", () => {
  //assuming we've added here two admins "admin1", "admin2" and "user1"
  const allAdmins = getUsers({ adminOnly: true });

  let admin1Found,
    adming2Found = false;

  allAdmins.forEach(aSingleUser => {
    if (aSingleUser === "user1") {
      assert.notEqual(aSingleUser, "user1", "A user was found and not admin");
    }
    if (aSingleUser === "admin1") {
      admin1Found = true;
    }
    if (aSingleUser === "admin2") {
      admin2Found = true;
    }
  });

  if (!admin1Found || !admin2Found) {
    throw new Error("Not all admins were returned");
  }
});

:clap: Doing It Right Example: Skimming through the following declarative test is a breeze

it("When asking for an admin, ensure only ordered admins in results", () => {
  //assuming we've added here two admins
  const allAdmins = getUsers({ adminOnly: true });

  expect(allAdmins)
    .to.include.ordered.members(["admin1", "admin2"])
    .but.not.include.ordered.members(["user1"]);
});

⚪ ️ 1.4 Stick to black-box testing: Test only public methods

:white_check_mark: Do: Testing the internals brings huge overhead for almost nothing. If your code/API delivers the right results, should you really invest your next 3 hours in testing HOW it worked internally and then maintain these fragile tests? Whenever a public behavior is checked, the private implementation is also implicitly tested and your tests will break only if