Question 1

You are a part of a team developing open-source software using GitHub Copilot. Your team is concerned about code duplication issues, especially with external dependencies. You’ve been asked to explore how GitHub Copilot’s duplication detector filter works to ensure that the code it suggests does not introduce duplicate code that may lead to bugs or licensing issues. Which of the following is the best explanation of how the duplication detector filter in GitHub Copilot works and how it helps prevent duplication issues?

Options :

A : GitHub Copilot-s duplication detector filter compares suggestions against open-source licenses and prevents suggestions that might infringe on licensing terms.

B : GitHub Copilot-s duplication detector filter automatically scans the code in your repository and alerts you if any suggestions are duplicates of existing code or external libraries.

C : The duplication detector filter blocks any code suggestions that match more than 150 characters from existing open-source repositories, preventing direct duplication of copyrighted code.

D : The duplication detector filter prevents the generation of identical code to what is already present in the repository, but only if the code being suggested is over 100 lines long.

Answer: C

Question 2

You are building a JavaScript application and using GitHub Copilot to assist with writing code. While working on a new feature, you notice that the suggestions are generally relevant but sometimes do not account for variables and functions that were previously defined in the same file. You begin to wonder how Copilot determines the context of a prompt when generating suggestions. Which of the following factors plays the most important role in determining the context for Copilot’s code suggestions?

Options :

A : The entire project directory, because Copilot scans all the project’s files to provide suggestions based on global context.

B : The prompt alone, as it gives Copilot all the information needed to generate accurate suggestions.

C : The code immediately preceding the prompt in the current file, as Copilot uses it to understand the local context.

D : The naming conventions of the variables and functions, because Copilot primarily uses those to generate suggestions.

Answer: C

Question 3

A team is tasked with modernizing a legacy application written in an outdated programming language with many inefficiencies. They plan to refactor portions of the application to make it more efficient and maintainable. The team decides to use GitHub Copilot to assist in the refactoring process. Which of the following strategies would best utilize GitHub Copilot to modernize the legacy codebase?

Options :

A : Use GitHub Copilot to generate documentation for the legacy codebase but avoid using it for code refactoring, since AI cannot understand the legacy code-s logic.

B : Use GitHub Copilot to suggest modern alternatives for outdated or inefficient code patterns, and then manually review and test the suggestions.

C : Depend on GitHub Copilot to detect and refactor performance bottlenecks without requiring further testing or validation.

D : Rely on GitHub Copilot to automatically rewrite the entire legacy codebase in a modern programming language.

Answer: B

Question 4

When using GitHub Copilot Chat, which of the following slash commands can be used to ask for additional information or clarification about an unfamiliar function in the code?

Options :

A : /define

B : /clarifyFunction

C : /debug

D : /trace

Answer: D

Question 5

You are a software developer tasked with building a new feature for an e-commerce platform that involves calculating the total price of items in a shopping cart, including tax and discounts. You are using JavaScript for the project. You're on a tight deadline and need to quickly implement this logic. You decide to use GitHub Copilot to assist in generating the initial code. Which of the following statements best describes how GitHub Copilot can help you in this scenario?

Options :

A : GitHub Copilot can provide code snippets for basic operations like calculating the total price, applying tax, and handling discounts, which can save the developer time by automating repetitive coding tasks.

B : GitHub Copilot can write the entire logic for the shopping cart calculation, including handling various tax laws and discount rules, without any developer input.

C : GitHub Copilot can completely replace manual testing by generating tests that cover all edge cases, including unexpected inputs and rare discount conditions.

D : GitHub Copilot can ensure that the logic follows best practices and is optimized for performance in large-scale e-commerce applications.

Answer: A

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