Why white-box testing examines code internals in Testing Fundamentals - Automation Benefits in Action

Verify white-box testing inspects code internals

Preconditions (2)

Step 1: Open the source code of the function 'calculate_discount' that applies a discount based on customer type

Step 2: Write a test that checks the function behavior for different customer types by inspecting internal logic branches

Step 3: Run the test and observe if all code paths are covered and verified

✅ Expected Result: The test should confirm that all internal branches of the function are tested and behave as expected

Automation Requirements - unittest

Assertions Needed:

assertEqual to verify function output for each input

assertTrue to confirm internal conditions if accessible

Best Practices:

Use clear and descriptive test method names

Test all logical branches inside the function

Keep tests independent and repeatable

Automated Solution

Testing Fundamentals

import unittest

# Function to test

def calculate_discount(customer_type, amount):
    if customer_type == 'regular':
        return amount * 0.9  # 10% discount
    elif customer_type == 'vip':
        return amount * 0.8  # 20% discount
    else:
        return amount  # no discount

class TestCalculateDiscount(unittest.TestCase):
    def test_regular_customer(self):
        self.assertEqual(calculate_discount('regular', 100), 90)

    def test_vip_customer(self):
        self.assertEqual(calculate_discount('vip', 100), 80)

    def test_unknown_customer(self):
        self.assertEqual(calculate_discount('guest', 100), 100)

if __name__ == '__main__':
    unittest.main()

This test script uses Python's unittest framework to check the calculate_discount function.

Each test method checks a different internal branch of the function: 'regular', 'vip', and unknown customer types.

Assertions verify the output matches expected discounts, ensuring the internal logic is tested.

This approach shows white-box testing by directly examining and validating the code's internal decision paths.

Common Mistakes - 3 Pitfalls

Testing only one input without covering all branches

Using print statements instead of assertions

Not isolating tests leading to dependencies

Bonus Challenge

Now add data-driven testing with 3 different customer types and amounts

Show Hint

Practice

1. Why does white-box testing focus on examining the internal code of a program?

easy

A. To verify the program's performance under load

B. To check the program's user interface for usability

C. To test the program without knowing its internal workings

D. To understand the program's structure and test specific code paths

Solution

1. Step 1: Understand white-box testing purpose

   White-box testing involves looking inside the code to test its logic and paths.

2. Step 2: Compare options with testing goals

   Only To understand the program's structure and test specific code paths matches the goal of testing internal code structure and paths.

3. Final Answer:

   To understand the program's structure and test specific code paths -> Option D

4. Quick Check:

   White-box tests code internals = D [OK]

Hint: White-box tests code internals, not UI or performance [OK]

Common Mistakes:

• Confusing white-box with black-box testing
• Thinking white-box tests UI or performance
• Ignoring the code structure in white-box testing

2. Which of the following is the correct syntax to write a white-box test case in Python using the unittest framework?

easy

A. class TestFunction(unittest.TestCase):
def test_case(self):
self.assertEqual(function_to_test(), expected_value)

B. def test_function():
assert function_to_test() == expected_value

C. function test_function() {
expect(function_to_test()).toBe(expected_value);
}

D.
function_to_test() == expected_value

Solution

1. Step 1: Identify Python unittest syntax

   Python unittest requires a class inheriting unittest.TestCase and methods starting with test_.

2. Step 2: Match options to unittest style

   class TestFunction(unittest.TestCase): def test_case(self): self.assertEqual(function_to_test(), expected_value) correctly defines a test class and method using self.assertEqual.

3. Final Answer:

   class TestFunction(unittest.TestCase): def test_case(self): self.assertEqual(function_to_test(), expected_value) -> Option A

4. Quick Check:

   Python unittest uses classes and assertEqual [OK]

Hint: Python unittest tests use classes and assertEqual method [OK]

Common Mistakes:

• Using plain functions without unittest class
• Confusing JavaScript or XML syntax with Python
• Missing self parameter in test methods

3. Consider this Python function and its white-box test case:

def is_even(n):
    if n % 2 == 0:
        return True
    else:
        return False

# Test case
assert is_even(3) == False
assert is_even(4) == True

What is the result of running this test case?

medium

A. First assertion fails, second passes

B. Both assertions fail

C. Both assertions pass, test succeeds

D. Syntax error in test case

Solution

1. Step 1: Evaluate is_even(3)

   3 % 2 is 1, so function returns False, matching assert is_even(3) == False.

2. Step 2: Evaluate is_even(4)

   4 % 2 is 0, so function returns True, matching assert is_even(4) == True.

3. Final Answer:

   Both assertions pass, test succeeds -> Option C

4. Quick Check:

   3 odd = False, 4 even = True [OK]

Hint: Check function output matches assertion values exactly [OK]

Common Mistakes:

• Assuming 3 is even
• Confusing modulus operator result
• Thinking assert causes syntax error

4. A white-box test case for a function has this code:

def calculate_discount(price):
    if price > 100:
        return price * 0.9
    else:
        return price * 0.95

# Test
assert calculate_discount(100) == 90

What is the problem with this test?

medium

A. The test expects wrong discount for price 100

B. The function has a syntax error

C. The test should use assertEqual instead of assert

D. The function does not handle negative prices

Solution

1. Step 1: Analyze function logic for price 100

   Price 100 is not greater than 100, so else branch applies: 100 * 0.95 = 95.

2. Step 2: Compare test assertion value

   Test expects 90, but function returns 95, so assertion fails.

3. Final Answer:

   The test expects wrong discount for price 100 -> Option A

4. Quick Check:

   Price 100 gets 5% discount, test expects 10% [OK]

Hint: Check boundary conditions carefully in tests [OK]

Common Mistakes:

• Assuming price 100 triggers > 100 condition
• Thinking assert is invalid in Python
• Ignoring else branch logic

5. You want to write white-box tests to cover all branches of this function:

def classify_number(x):
    if x > 0:
        if x % 2 == 0:
            return 'Positive even'
        else:
            return 'Positive odd'
    elif x < 0:
        return 'Negative'
    else:
        return 'Zero'

Which set of test inputs covers all branches?

hard

A. [2, 4, 6]

B. [1, 2, 0, -1]

C. [0, -5]

D. [-1, 0, 1]

Solution

1. Step 1: Identify branches to cover

   Branches: x > 0 with even and odd, x < 0, and x == 0.

2. Step 2: Check test inputs for coverage

   Input 1 covers positive odd, 2 covers positive even, 0 covers zero, -1 covers negative.

3. Final Answer:

   [1, 2, 0, -1] -> Option B

4. Quick Check:

   All branches tested by these inputs [OK]

Hint: Test positive even, positive odd, zero, and negative separately [OK]

Common Mistakes:

• Missing positive odd or even cases
• Not testing zero case
• Assuming fewer inputs cover all branches