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Scenario:

You’ve designed an algorithm in pseudocode, but now you need to turn it into a working Python function. Instead of writing it line by line manually, your AI assistant can convert pseudocode into executable code.

Step 0: Define Your Goal

Example pseudocode for factorial:

FUNCTION factorial(n):
    IF n < 0 THEN
        RETURN error "Input must be non-negative"
    END IF
    result = 1
    FOR i = 2 TO n
        result = result * i
    END FOR
    RETURN result
END FUNCTION

Goal: Convert this pseudocode into Python code.

Step 1: Craft the AI Prompt

Treat AI as a developer who understands pseudocode. Include:

1. The pseudocode
2. Target programming language
3. Optional: include comments or input validation

Example Prompt:

Convert the following pseudocode into Python. 
Include input validation and comments explaining each step.

Step 2: AI Output Example

def factorial(n: int) -> int:
    """
    Calculate the factorial of a non-negative integer n.
    """
    if n < 0:
        raise ValueError("Input must be non-negative")  # Handle invalid input
    result = 1
    for i in range(2, n+1):
        result *= i  # Multiply each number up to n
    return result

Test:

print(factorial(5))  # 120
print(factorial(0))  # 1
# print(factorial(-1))  # Raises ValueError

Step 3: Mini Lab Challenges

1. Convert pseudocode for is_prime(n) into Python.
2. Convert pseudocode for Fibonacci sequence (iterative and recursive versions).
3. Convert a pseudocode snippet into JavaScript or Java.
4. Ask AI to add comments explaining edge cases.

Step 4: Pro Tips

• Clearly define inputs, outputs, and conditions in pseudocode before asking AI.
• Specify the target language for translation.
• Include instructions for comments, error handling, or type hints.
• Iteratively refine AI-generated code to handle all edge cases.

Lab Summary

• AI can turn algorithm ideas in pseudocode into executable code efficiently.
• Clear prompts + defined pseudocode = accurate translation.
• Always test AI-generated code and refine as needed.
• This skill is especially useful for interviews, collaborative projects, and algorithm learning.