← VCE Software Development U3O1

Emerging trend: AI code generation tools

Using AI tools, like editor assistants and chatbots, to turn plain-English prompts into program code. It saves time, but the code must still be checked and tested by the programmer.

Part of: VCE Software Development - U3O1 - Programming — Module 181, VCE Software Development - U4O1 - development and evaluation — Module 126, VCE Software Development - U4O2 - Cyber Security: secure software development practices — Module 113

Understanding Emerging trend: AI code generation tools in VCE Software Development U3O1

What it does: A chat prompt in natural language is how a chatbot is asked to generate code, which is the core idea of chat-based generation. An assert test checks that generated code gives the expected output, because AI can produce code that looks right but is wrong. Editor assistants sit inside the coding environment and suggest or complete code while you work. AI is quick at routine, common patterns. It cannot guarantee that its code is correct or bug-free. AI works from the prompt it is given and can miss project-specific requirements or constraints. Good prompts help, but gaps can remain. AI can save time writing code, but programmers still need to understand, review and test what it produces.

Common mistakes: The AI-generated function takes one list, but this call passes three separate numbers. It should be print(average([2, 4, 6])). A comma is missing between the two arguments, which causes a syntax error. It should be print('Words:', count).

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This module's key terms are also in a printable crossword (Modules 178–193) and word search (Modules 168–193).

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Learning

Duo

What does an AI code generation tool turn into program code?

A plain-English (natural-language) promptA compiled machine-code file

Matches

# AI wrote this, so it must be correct. Submit it without running it.

↓

Trusting AI-generated code without checking or testing it. It can contain logic errors, bugs or out-of-date methods.

Applying

Meanings

Term

AI code generation

Meaning

Using AI tools, like editor assistants and chatbots, to turn plain-English prompts into program code. It saves time, but the code must still be checked and tested by the programmer.

Practice

def average(numbers):

Testing

Gaps

add(a, b):

Check Answer

Spots

3 return total / len(nums)

4print(average(2, 4, 6))

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Quick Questions

1. What does an AI code generation tool turn into program code?

A. A plain-English (natural-language) prompt ✓

B. A compiled machine-code file

AI code generation tools take a prompt written in everyday language and produce code. The programmer describes what is needed.

2. Which one is an example of a code assistant in an editor?

A. A spell checker that fixes essays in a word processor

B. Code completion that suggests the next lines as you type ✓

Editor assistants sit inside the coding environment and suggest or complete code while you work.

3. Chat-based code generation works by:

A. Typing a request into a chatbot and getting code back in the reply ✓

B. Dragging blocks onto a canvas to build the code by hand

With chat-based tools, you describe the task in a conversation and the chatbot replies with code you can copy and review.

4. AI is generally good at which task in programming?

A. Drafting repetitive boilerplate code quickly ✓

B. Guaranteeing code is free of every bug

AI is quick at routine, common patterns. It cannot guarantee that its code is correct or bug-free.

5. AI-generated code should be:

A. Trusted and used without checking because AI is never wrong

B. Checked and tested by the programmer before use ✓

AI can produce code that looks right but contains errors, so the programmer is still responsible for reviewing and testing it.

Match the Pairs

# Write a function that returns the average of a list → A natural-language prompt written as a comment, which an editor assistant can turn into a suggested function

Tab key to accept a suggestion → Accepting the code that an editor's AI code completion tool has proposed as you type

Chat-based code generation: describe the task in plain English and the chatbot replies with program code → Prompt: Write a Python function that checks if a number is prime

AI is good at repetitive boilerplate code, but the programmer must still test the result → assert average([2, 4, 6]) == 4

# AI wrote this, so it must be correct. Submit it without running it. → Trusting AI-generated code without checking or testing it. It can contain logic errors, bugs or out-of-date methods.

Prompt: Make my app better → The prompt is vague. AI tools generate better code from clear, specific prompts that state the language, inputs and expected output.

Key Term

AI code generation

Using AI tools, like editor assistants and chatbots, to turn plain-English prompts into program code. It saves time, but the code must still be checked and tested by the programmer.

Fill in the Blanks

1. # Prompt: add two numbers def add(a, b): return a + b

Hint: Type the keyword that starts a function definition in the code the AI generated.

2. # Generated by an AI assistant def area(w, h): return w * h

Hint: Type the second parameter name, which the function body uses in its calculation.

3. prompt = input("Ask: ") reply = chatbot(prompt) print(reply)

Hint: Type the function name that displays the code the chatbot returned.

4. def double(n): return n * 2 assert double(4) == 8

Hint: Type the keyword used to test that AI-generated code gives the expected result.

5. result = average([2, 4, 6]) if result == 4: print("Test passed")

Hint: Type the comparison operator that checks whether the AI code's result equals the expected value.

Spot the Error

Question 1

A def average(nums):

B total = sum(nums)

C return total / len(nums)

D print(average(2, 4, 6))

Line D — The AI-generated function takes one list, but this call passes three separate numbers. It should be print(average([2, 4, 6])).

Question 2

A prompt = input('Describe: ')

B words = prompt.split()

C count = len(words)

D print('Words:' count)

Line D — A comma is missing between the two arguments, which causes a syntax error. It should be print('Words:', count).

Question 3

A def is_even(n):

B remainder = n % 2

C return remainder = 0

D print(is_even(10))

Line C — A single = assigns a value and is not allowed in a return. To compare, the AI code should use ==: return remainder == 0.

Question 4

A tips = ['test', 'review']

B for tip in tips

C print(tip)

Line B — A for statement must end with a colon. It should be for tip in tips:. Reading AI code carefully helps you spot small syntax slips like this.

Question 5

A def greet(name):

B return 'Hello, ' + nme

C print(greet('Sam'))

Line B — The variable nme does not exist, so Python raises a NameError. The parameter is called name. AI code can contain typos, so check it.

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