IGCSE Computer Science 0478 - Algorithm Design and Problem-Solving

Objective: Suggest and Apply Suitable Test Data

This section focuses on the crucial aspect of test data in algorithm design. Effective test data is essential to ensure an algorithm functions correctly under various conditions. It's not enough to simply write an algorithm; you must rigorously test it to identify and fix errors.

Why is Test Data Important?

• Error Detection: Test data helps uncover bugs and errors in the algorithm's logic.
• Algorithm Validation: Confirms the algorithm produces the expected output for valid inputs.
• Boundary Condition Testing: Checks how the algorithm handles edge cases (minimum, maximum, empty inputs).
• Robustness: Ensures the algorithm is resilient to unexpected or invalid inputs.

Types of Test Data

• Normal/Typical Data: Represents the expected input the algorithm is designed to handle.
• Boundary Data: Values at the edges of the valid input range (e.g., minimum, maximum, zero).
• Invalid Data: Inputs that are outside the expected range or format (e.g., negative numbers when positive are expected, empty strings).
• Error Data: Designed to trigger specific error handling mechanisms within the algorithm.

Designing Test Data: A Systematic Approach

1. Define Input Constraints: Clearly identify the valid and invalid input values.
2. Identify Boundary Conditions: Determine the minimum, maximum, and zero values for numeric inputs, and the shortest and longest possible string lengths.
3. Create a Test Case Table: Organize test data into a table for clarity and completeness.
4. Consider Edge Cases: Think about unusual or unexpected inputs that might cause problems.
5. Test for Error Handling: Include data that should trigger error messages or exception handling.

Example: Algorithm to Calculate the Average of a List of Numbers

Let's consider an algorithm that calculates the average of a list of numbers. Here's a table outlining suitable test data:

Test Case ID	Input Data	Expected Output	Test Type
TC1	{1, 2, 3, 4, 5}	3.0	Normal Data
TC2	{10, 20, 30, 40, 50}	30.0	Normal Data
TC3	{1, 2, 3, 4}	2.5	Normal Data
TC4	{0, 0, 0, 0}	0.0	Boundary Data (Zero)
TC5	{1, 1000000, 2}	500000.5	Boundary Data (Large Numbers)
TC6	{}	Error Message (e.g., "Empty list")	Invalid Data (Empty List)
TC7	{-1, 1, 0}	0.0	Normal Data (Negative Numbers)
TC8	{1.5, 2.5, 3.5}	2.5	Normal Data (Floating Point Numbers)

Explanation of Test Cases:

• TC1-TC3: These are typical lists of numbers to ensure the algorithm works correctly with standard input.
• TC4: Tests the algorithm's behavior when all input numbers are zero.
• TC5: Tests the algorithm's ability to handle very large numbers.
• TC6: Tests the algorithm's error handling for an empty list. A good algorithm should provide an appropriate error message or handle the empty list gracefully.
• TC7: Tests the algorithm's ability to handle negative numbers.
• TC8: Tests the algorithm's ability to handle floating-point numbers.

Important Considerations:

The specific test data you choose will depend on the requirements of the algorithm. Always consider potential edge cases and invalid inputs. A well-designed set of test data will significantly increase your confidence in the correctness of your algorithm.