GH-300 Exam Dumps - GitHub Copilot Exam

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Question # 17

Which of the following does GitHub Copilot ' s LLM derive context from when producing a response?

Frequency of commits to the repository

Syntax highlighting scheme of the code in the IDE

Neighboring or related files within a project

Version control system integrated with the IDE

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Question # 18

How does GitHub Copilot Chat help to fix security issues in your codebase?

By enforcing strict coding standards that prevent the introduction of vulnerabilities.

By providing detailed reports on the security vulnerabilities present in the codebase.

By annotating the given suggestions with known vulnerability patterns.

By automatically refactoring the entire codebase to remove vulnerabilities.

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Question # 19

How can GitHub Copilot assist with code refactoring tasks?

GitHub Copilot can fix syntax errors without user input.

GitHub Copilot can automatically rewrite code to follow best practices.

GitHub Copilot can suggest refactoring improvements for better code quality.

GitHub Copilot can remove unnecessary files from the project directory.

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Question # 20

Which of the following statements correctly describes how GitHub Copilot Individual uses prompt data? (Each correct answer presents part of the solution. Choose two.)

Prompt data is stored unencrypted for faster processing.

Prompt data is used internally by GitHub for improving the search engine.

Prompt data is used to train machine learning models for better code suggestions.

Real-time user input helps generate context-aware code suggestions.

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Question # 21

What are the different ways to give context to GitHub Copilot to get more precise responses? (Each correct answer presents part of the solution. Choose two.)

Utilize to interpret developer ' s thoughts and intentions without any code or comments.

Engage with chat participants such as @workspace to incorporate collaborative context into the responses.

Access developer ' s previous projects and code repositories to understand their coding style without explicit permission.

Utilize chat variables like *file to anchor the conversation within the specific context of the files or editors in use.

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Question # 22

Are there any limitations to consider when using GitHub Copilot for code refactoring?

GitHub Copilot may not always produce optimized or best-practice code for refactoring.

GitHub Copilot can only be used with a limited set of programming languages.

GitHub Copilot always produces bug-free code during refactoring.

GitHub Copilot understands the context of your entire project and refactors code accordingly.

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Question # 23

Identify the right use cases where GitHub Copilot Chat is most effective. (Each correct answer presents part of the solution. Choose two.) Â

Create a technical requirement specification from the business requirement documentation

Explain a legacy COBOL code and translate the code to another language like Python.

Creation of a unit test scenario for newly developed Python code

Creation of end-to-end performance testing scenarios for a web application

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Question # 24

How can GitHub Copilot be limited when it comes to suggesting unit tests?

GitHub Copilot can generate all types of unit tests, including those for edge cases and complex integration scenarios.

GitHub Copilot primarily suggests basic unit tests that focus on core functionalities, often requiring additional input from developers for comprehensive coverage.

GitHub Copilot can handle any complexity in code and automatically generate appropriate unit tests.

GitHub Copilot ' s limitations in generating unit tests can vary based on the IDE version you are using.

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