Question 1

You are working on a project to build a loan approval system for a bank using GitHub Copilot to speed up development. The system will be used to make important financial decisions, and your company is focused on ensuring Responsible AI usage. What steps should you take to ensure transparency and accountability when using Copilot for this project?

Options :

A : Allow Copilot to suggest code but ensure all suggestions are logged and reviewed during code audits to maintain transparency and ensure accountability.

B : Document every decision Copilot makes during code generation and flag any code that relates to sensitive areas like loan eligibility criteria.

C : Since Copilot-generated code is likely compliant with industry standards, you don’t need to perform additional logging or auditing of AI-generated code.

D : Rely on Copilot’s code suggestions without documenting how the generated code was used, as the system’s focus is on speeding up development.

Answer: A

Question 2

You are a Python developer working on a project where you need to automate data entry into an Excel sheet using the openpyxl library. You plan to use GitHub Copilot to assist with writing a Python function that adds a row of data to an existing Excel file. You want to ensure that your prompt is specific enough to produce accurate and helpful code suggestions. Which of the following prompts would be the most effective to generate code using GitHub Copilot for adding a row of data to an Excel file using the openpyxl library?

Options :

A : "Use openpyxl to write a row of data into the Excel file named 'data.xlsx', in the 'Sheet1' sheet, starting from the first empty row."

B : "How to use openpyxl in Python?"

C : "Write a function that adds data to a file."

D : "Add data to an Excel sheet."

Answer: A

Question 3

You are working on a Python web application that processes and serves large datasets. The performance of a key function responsible for fetching and processing the data is critical. You plan to optimize this function to handle larger loads efficiently. You're relying on GitHub Copilot for code suggestions to improve performance, particularly focusing on reducing the time complexity of your function. Here is your initial code:

def fetch_and_process_data(data_list):

result = []

for data in data_list:

processed_data = process(data)

result.append(processed_data)

return result

Which of the following GitHub Copilot suggestions would most effectively optimize the performance of this function?

Options :

A :

def fetch_and_process_data(data_list):
result = set()
for data in data_list:
processed_data = process(data)
result.add(processed_data)
return result

B :

def fetch_and_process_data(data_list):
return map(process, data_list)

C :

def fetch_and_process_data(data_list):
return [process(data) for data in data_list]

D :

def fetch_and_process_data(data_list):
for data in data_list:
result = process(data)
return result

Answer: C

Question 4

As a junior developer, you’ve recently started using GitHub Copilot Chat to assist in your coding tasks. You want to ensure you’re getting the best out of the AI assistant while maintaining code quality, security, and efficiency. During a session, Copilot suggests a code snippet. Before accepting it, what best practice should you follow?

Options :

A : Disable all linting tools to avoid conflicts with Copilot-s suggestions

B : Review the suggested code for security vulnerabilities and bugs

C : Copy the code from Copilot and paste it directly into your production codebase

D : Always accept the first suggestion without reviewing the code

Answer: B

Question 5

You are using GitHub Copilot to help generate boilerplate code for a web application that interacts with a database to store and retrieve user-submitted information. The code suggested by Copilot works well for basic functionality, but you are concerned about potential security vulnerabilities, particularly regarding SQL injection attacks. What is the most responsible approach to ensure the Copilot-suggested code is secure before implementing it in your production environment?

Options :

A : Review the Copilot-generated code carefully for common security vulnerabilities, such as SQL injection, and test it with both normal and malicious inputs.

B : Assume that Copilot-generated code follows secure coding practices, since it has been trained on a large amount of open-source code.

C : Use the Copilot-suggested code in your production environment as-is, but monitor it closely for any security incidents after deployment.

D : Use Copilot’s code suggestions only for non-critical parts of the application, assuming that security issues are less important for these sections.

Answer: A

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