Testing Strategies

This lesson covers software testing strategies for the OCR A-Level Computer Science (H446) specification. Testing ensures that software is correct, reliable, and meets its requirements. You need to understand different testing types, techniques, and tools.

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Why Test Software?

Testing is essential because:

• It identifies bugs and defects before software reaches users.
• It verifies that software meets its requirements.
• It ensures software is reliable, secure, and performant.
• It reduces the cost of fixing errors -- bugs found early are much cheaper to fix.
• It builds confidence that the software works as expected.

Exam Tip: Know the difference between verification ("Are we building the product right?") and validation ("Are we building the right product?"). Testing contributes to both.

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Types of Testing

Unit Testing

Unit testing tests individual components (functions, methods, or classes) in isolation from the rest of the system.

def add(a: int, b: int) -> int:
    return a + b

# Unit tests
assert add(2, 3) == 5
assert add(-1, 1) == 0
assert add(0, 0) == 0

Advantage	Disadvantage
Fast to run	Does not test component interactions
Easy to isolate and fix bugs	Many tests needed for full coverage
Can be automated	May miss integration-level bugs

Integration Testing

Integration testing tests the interactions between components that have already been unit tested. It verifies that modules work correctly when combined.

Approach	Description
Top-down	High-level modules first; uses stubs for untested lower modules.
Bottom-up	Low-level modules first; uses drivers for higher modules.
Big bang	All modules integrated at once (risky -- hard to isolate faults).

System Testing

System testing tests the complete, integrated system against the original requirements specification. It covers both functional and non-functional requirements.

Acceptance Testing

Acceptance testing is performed by end users or clients to verify the software meets their needs.

Type	Description
Alpha testing	Internal testing within the development organisation.
Beta testing	Testing by a limited group of external users before public release.

Exam Tip: Know the testing order: Unit -> Integration -> System -> Acceptance. Each level tests at a broader scope.

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Test Data Categories

Category	Description	Example (age field, valid: 0-120)
Normal (valid)	Data within the expected range	25, 50, 100
Boundary	Data at the edges of valid ranges	0, 1, 119, 120
Erroneous (invalid)	Data outside the range or wrong type	-1, 121, "abc", 999

Boundary Testing Example

For a valid range of 1 to 100:

Test Value	Category	Expected Result
0	Erroneous (below min)	Rejected
1	Boundary (minimum)	Accepted
2	Normal (above min)	Accepted
50	Normal	Accepted
99	Normal (below max)	Accepted
100	Boundary (maximum)	Accepted
101	Erroneous (above max)	Rejected

Exam Tip: Always include boundary values in your test plans. Many mark schemes specifically award marks for boundary data at both the minimum and maximum.

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Test-Driven Development (TDD)

TDD is a development approach where tests are written before the code.

The TDD Cycle (Red-Green-Refactor)

1. Red: Write a failing test for the desired behaviour.
2. Green: Write the minimum code to make the test pass.
3. Refactor: Improve the code while keeping all tests passing.

# Step 1: Write failing test
def test_is_palindrome():
    assert is_palindrome("racecar") == True
    assert is_palindrome("hello") == False
    assert is_palindrome("") == True

# Step 2: Write minimum code to pass
def is_palindrome(text: str) -> bool:
    return text == text[::-1]

# Step 3: Refactor if needed

Benefits of TDD

• Ensures thorough test coverage from the start.
• Encourages simple, focused code.
• Tests serve as living documentation.
• Bugs are caught immediately during development.

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Black-Box vs White-Box Testing