Testing makes your test code more elegant: 10 principles for writing high-quality test scripts

In software development, high-quality test scripts are the key to ensuring software quality. However, writing good test scripts is not an easy task. Below, we will discuss how to write elegant and high-quality test scripts through several basic principles.

1. Clear test objectives

First, we need to clarify the goals of each test. Test scripts need to have clear goals so that they can be tested in a targeted manner, rather than blindly testing a wide range. For example, a test script for user login function should clearly test user name, password input, and login results under different circumstances.

For example:

def test_login():
    assert login('username', 'password') == 'Success'
    assert login('', 'password') == 'Username cannot be empty'
    assert login('username', '') == 'Password cannot be empty'

2. Concise and clear

Test code needs to be concise and clear. Complicated test code is not only difficult to understand and maintain, it can also hide potential problems. Try to use clear naming, avoid unnecessary complex logic, and make your code as clear as possible.

For example, it is not recommended to write:

def test_p():
    p = get_p()
    assert p == True

It is recommended to write like this:

def test_is_user_logged_in():
    is_logged_in = check_user_logged_in_status()
    assert is_logged_in == True

3. Repeatability

A good test script should be highly repeatable. This means that no matter when the test script is run, the results should always be the same as long as it is in the same environment. In order to achieve this, we need to try to avoid or control factors that may cause changes in the results, such as time, random numbers, etc.

For example, it is not recommended to write:

def test_current_time():
    assert get_current_time() > '2023-01-01'

It is recommended to write like this:

def test_fixed_time():
    fixed_time = '2023-01-01'
    assert get_fixed_time(fixed_time) == '2023-01-01'

4. Make full use of assertions

Reasonable use of assertions can help us express test intent more clearly and locate problems more precisely. Each test case should test only one concept and use assertions to verify that concept. Doing this can help us better understand why tests are failing.

For example, it is not recommended to write:

def test_login():
    result = login('username', 'password')
    if result != 'Success':
        print('Login failed.')

It is recommended to write like this:

def test_login():
    result = login('username', 'password')
    assert result == 'Success', 'Login failed.'

5. Independence

Each test case should be self-contained and not depend on the results of other test cases. This ensures that the failure of any test case does not affect other test cases, while also making each test case easier to understand and maintain.

For example, it is not recommended to write:

def test_user():
    create_user('username', 'password')
    assert login('username', 'password') == 'Success'

It is recommended to write like this:

def test_create_user():
    assert create_user('username', 'password') == 'Success'

def test_login():
    setup_user('username', 'password')
    assert login('username', 'password') == 'Success'

6. Strengthen error handling

A good test script should be able to handle various expected errors. When an error occurs, the test script should provide enough information to help us quickly locate and solve the problem.

For example, it is not recommended to write:

def test_login():
    result = login('username', 'password')
    assert result == 'Success'

It is recommended to write like this:

def test_login():
    result = login('username', 'password')
    assert result == 'Success', f'Expected Success, but got {result}'

Seven, consider the boundary conditions

When writing test scripts, all possible scenarios, including boundary conditions, should be considered. This allows for more thorough testing of the stability and robustness of the code.

For example:

def test_password_length():
    short_password = '123'
    long_password = '12345678901234567890'
    assert register('username', short_password) == 'Password is too short'
    assert register('username', long_password) == 'Password is too long'

8. Structuring and Modularization

Test scripts should have a clear structure and modular design, which improves code readability and maintainability. For example, you can encapsulate repetitive operations or complex steps into functions or modules to simplify test scripts.

For example, it is recommended to write:

def setup_user(username, password):
    create_user(username, password)
    activate_user(username)

def test_login():
    setup_user('username', 'password')
    assert login('username', 'password') == 'Success'

9. Good Code Comments

Good code comments can help readers understand your code, especially those complex or critical parts. However, comments should not be excessive, otherwise it may affect the readability of the code.

For example:

def test_login():
    # Setup user for the test
    setup_user('username', 'password')
    
    # Try to login and check the result
    assert login('username', 'password') == 'Success'

Ten, consider the performance impact

While the main goal of a test script is to check functionality and find problems, it should also be optimized for performance as much as possible. If your test scripts run very slowly, it may greatly affect the progress of the entire test and development.

For example, you can use some performance analysis tools to find performance bottlenecks in your test scripts and try to optimize them.

The suggestions and examples above are just a part of how to write elegant and high-quality test scripts. In the actual writing process, you need to constantly explore and learn according to the actual needs and environment. Good luck writing better test scripts!

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