Testing Made Easy: Unit and Integration Testing in Java Backends#

JUnit#

Most Java developers start their testing journey with JUnit. It’s a lightweight framework that provides:

• Annotations such as @Test, @BeforeEach, and @AfterEach.
• Assertion methods for validating test results.
• Integration with most IDEs (Eclipse, IntelliJ, etc.).

TestNG#

TestNG is known for its advanced features:

• Parallel tests: Run multiple tests simultaneously.
• Dependency testing: Control the order tests run in.
• Data-driven testing: Use multiple data sets for the same test method.

Mockito#

Mockito is a mocking framework typically used to create test doubles for classes or interfaces, helping isolate units under test. Key features:

• Creating mocks using mock(ClassName.class).
• Verifying interactions using verify().
• Stubbing methods to return predetermined data.

Spring Test#

For developers using the Spring Framework, Spring Test includes:

• Integration with JUnit/TestNG.
• Mocking of Spring Boot applications with the @SpringBootTest annotation.
• Utilities for testing web applications (e.g., MockMvc).

Below is a quick table summarizing each framework’s primary use case:

What Are Unit Tests?#

A unit test checks the smallest testable parts (units) of your application—usually a method or class. The goal is to verify that each part functions correctly in isolation from the rest. They typically:

• Run quickly.
• Have minimal external dependencies.
• Are easy to set up and tear down.

Anatomy of a Unit Test#

Consider a simple method that adds two integers:

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public class Calculator {
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    public int add(int a, int b) {
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        return a + b;
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    }
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}

A basic JUnit test:

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import static org.junit.jupiter.api.Assertions.assertEquals;
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import org.junit.jupiter.api.Test;
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public class CalculatorTest {
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    @Test
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    void testAdd() {
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        Calculator calculator = new Calculator();
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        int result = calculator.add(2, 3);
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        assertEquals(5, result, "2 + 3 should equal 5");
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    }
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}

Here’s what’s happening:

1. Setup: We instantiate the Calculator class.
2. Action: We call the add method with fixed inputs.
3. Assertion: We compare the result against the expected value (5).

Test Fixtures and the Lifecycle#

JUnit provides annotations to set up and clean resources. For example, @BeforeEach to initialize common variables, and @AfterEach to release resources after each test.

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import static org.junit.jupiter.api.Assertions.assertEquals;
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import org.junit.jupiter.api.BeforeEach;
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import org.junit.jupiter.api.AfterEach;
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import org.junit.jupiter.api.Test;
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public class CalculatorTest {
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    private Calculator calculator;
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    @BeforeEach
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    void setUp() {
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        calculator = new Calculator();
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    }
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    @AfterEach
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    void tearDown() {
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        // Clean up resources if needed
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    }
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    @Test
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    void testAdd() {
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        int result = calculator.add(10, 5);
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        assertEquals(15, result);
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    }
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}

Clear Test Names#

Make sure your test methods clearly describe the scenario being tested. For example:

• shouldAddPositiveNumbersCorrectly()
• shouldAddNegativeNumbersCorrectly()

This helps future maintainers quickly understand the test’s intention.

Use Parameterized Tests#

When you want to test multiple inputs without repeating code, JUnit’s @ParameterizedTest can help:

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import static org.junit.jupiter.api.Assertions.assertEquals;
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import org.junit.jupiter.params.ParameterizedTest;
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import org.junit.jupiter.params.provider.CsvSource;
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public class CalculatorTest {
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    @ParameterizedTest
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    @CsvSource({
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        "1,2,3",
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        "2,3,5",
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        "-1,-4,-5"
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    })
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    void testAddParameterized(int a, int b, int expected) {
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        Calculator calculator = new Calculator();
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        assertEquals(expected, calculator.add(a, b));
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    }
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}

Mocking Dependencies#

If a class relies on external services (e.g., a database, network call), you can mock or stub those dependencies:

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public class WeatherService {
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    public String getCurrentWeather() {
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        // Imagine this calls an external API
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        return "Sunny";
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    }
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}
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public class WeatherController {
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    private WeatherService weatherService;
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    public WeatherController(WeatherService weatherService) {
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        this.weatherService = weatherService;
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    }
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    public String getWeatherMessage() {
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        return "Today is " + weatherService.getCurrentWeather();
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    }
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}

In your test:

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import org.junit.jupiter.api.Test;
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import org.mockito.Mockito;
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import static org.junit.jupiter.api.Assertions.assertEquals;
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public class WeatherControllerTest {
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    @Test
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    void testGetWeatherMessage() {
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        WeatherService mockService = Mockito.mock(WeatherService.class);
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        Mockito.when(mockService.getCurrentWeather()).thenReturn("Cloudy");
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        WeatherController controller = new WeatherController(mockService);
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        String message = controller.getWeatherMessage();
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        assertEquals("Today is Cloudy", message);
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    }
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}

What Are Integration Tests?#

While unit tests focus on individual methods or classes, integration tests check if multiple components work together as intended. This can cover:

• Multiple classes within the same module.
• Full subsystems within your application.
• Database interactions and other external resources (if required).

Ideal integration tests balance speed with realism. They often:

• Run slower than unit tests because they involve external systems or frameworks.
• Provide higher confidence in how features work end-to-end.

When to Use Integration Tests#

Use integration tests to verify:

• Inter-module communication: For instance, does your controller correctly call the service layer?
• Database interactions: Are SQL queries executed as expected?
• API endpoints: For example, testing endpoints in a REST application.

Spring Boot Example#

If you’re using Spring Boot, you can use @SpringBootTest to load the entire application context. This offers a near-production environment without deploying:

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@SpringBootTest(webEnvironment = SpringBootTest.WebEnvironment.RANDOM_PORT)
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public class WeatherIntegrationTest {
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    @Autowired
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    private TestRestTemplate restTemplate;
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    @Test
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    void testGetWeatherEndpoint() {
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        String response = restTemplate.getForObject("/weather", String.class);
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        assertEquals("Today is Sunny", response);
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    }
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}

In the above:

• @SpringBootTest(webEnvironment = SpringBootTest.WebEnvironment.RANDOM_PORT) tells Spring Boot to start the web server on a random port.
• TestRestTemplate is injected to simplify HTTP calls to the running application.
• We then call the /weather endpoint to verify if we get the expected response.

Testing Database Interactions#

When testing database interactions, you’ll often use in-memory databases (e.g., H2) for speed and simplicity. For instance:

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@ExtendWith(SpringExtension.class)
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@SpringBootTest
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@AutoConfigureTestDatabase(replace = AutoConfigureTestDatabase.Replace.NONE)
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@TestPropertySource(locations="classpath:application-test.properties")
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public class UserRepositoryIntegrationTest {
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    @Autowired
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    private UserRepository userRepository;
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    @Test
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    void testSaveUser() {
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        User user = new User();
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        user.setName("Alice");
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        userRepository.save(user);
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        List<User> users = userRepository.findAll();
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        assertEquals(1, users.size());
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        assertEquals("Alice", users.get(0).getName());
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    }
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}

In application-test.properties, you might configure an in-memory DB:

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spring.datasource.url=jdbc:h2:mem:testdb
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spring.datasource.driverClassName=org.h2.Driver
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spring.jpa.hibernate.ddl-auto=create

Behavior-Driven Development (BDD)#

BDD encourages writing tests in a human-readable format, often using tools like Cucumber or JBehave. Instead of writing traditional JUnit tests, you write scenarios:

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Feature: Weather Forecast
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  Scenario: User checks current weather
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    Given a user is on the weather page
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    When the user requests today's weather
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    Then they should see "Today is Sunny"

Under the hood, these scenarios map to step definitions in Java. BDD helps maintain a clear, shared understanding of requirements.

Test Data Builders#

Complex objects can be cumbersome to create for tests. A “Test Data Builder” pattern ensures consistent, readable setup. Instead of:

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User user = new User();
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user.setName("Bob");
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user.setAge(28);
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user.setLocation("New York");
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// ... more fields ...

Use a builder:

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public class UserBuilder {
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    private String name = "Alice";
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    private int age = 30;
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    private String location = "London";
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    public UserBuilder withName(String name) {
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        this.name = name;
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        return this;
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    }
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    public UserBuilder withAge(int age) {
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        this.age = age;
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        return this;
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    }
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    public UserBuilder withLocation(String location) {
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        this.location = location;
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        return this;
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    }
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    public User build() {
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        User user = new User();
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        user.setName(name);
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        user.setAge(age);
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        user.setLocation(location);
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        return user;
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    }
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}

In tests:

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User user = new UserBuilder().withName("Bob").withAge(28).build();

Code Coverage Tools#

Tools like Jacoco or Cobertura integrate with build tools (Maven, Gradle) to measure coverage. Strive to cover critical paths, but remember coverage alone doesn’t guarantee quality tests.

Why CI/CD Matters#

Continuous Integration ensures that every time code is committed, a pipeline automatically compiles the application and runs all tests. This provides immediate feedback if something breaks. Continuous Delivery extends this by automating deployment to staging or production, ensuring frequent and reliable releases.

Common CI/CD Platforms:

• Jenkins
• GitLab CI
• GitHub Actions
• CircleCI

Typical Stages in a Pipeline#

1. Compile: Build the Java application (Maven, Gradle, etc.).
2. Unit Tests: Run fast, isolated unit tests.
3. Integration Tests: Spin up a test environment (in-memory DB, mock services) to ensure components work together.
4. Coverage and Code Quality Checks: Tools like Jacoco, SonarQube.
5. Deployment: Deploy to a staging or production environment, if all tests pass.

Creating a Testing Pyramid#

The “testing pyramid” suggests having more unit tests than integration tests and more integration tests than end-to-end tests.

1. Unit Tests (foundation, largest number): Fastest, cover most functionality.
2. Integration Tests: Middle layer, fewer in number.
3. End-to-End Tests (tip of the pyramid): High-level tests requiring entire systems.

Modularization#

For big projects, break them into smaller modules or microservices. Each module can have its own unit and integration tests. Cross-service interaction should be tested via contract tests or end-to-end tests.

Contract Testing#

If you have multiple services interacting, contract tests (using frameworks like Pact) ensure both provider and consumer agree on the request/response structure. This reduces the need for complex integration environments.

WireMock#

Helps create mock HTTP servers. Useful when your Java application depends on external REST APIs. You can simulate various responses (success, error, delays) without hitting the real service.

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WireMockServer wireMockServer = new WireMockServer(8080);
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wireMockServer.start();
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wireMockServer.stubFor(get(urlEqualTo("/weather"))
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    .willReturn(aResponse()
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        .withStatus(200)
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        .withBody("Cloudy")));
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// Test code here
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wireMockServer.stop();

Mockito Alternatives#

• EasyMock: Another mocking library with a different syntax.
• PowerMock: Lets you mock static methods, final classes—useful in legacy systems, but should be a last resort.

UI and E2E Testing Tools#

• Selenium WebDriver: Automates web browsers for end-to-end testing.
• Cypress: Modern tool for front-end testing.

(In large enterprise setups, keep UI tests in separate repositories or folders to avoid cluttering your backend codebase.)