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Microsoft
GitHub Administrator
GH-300
GitHub Copilot Exam Questions and Answers

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Viewing questions 31-40 out of questions

Questions # 31:

What is the correct way to access the audit log events for GitHub Copilot Business?

Options:

Navigate to the Security tab in the organization's GitHub settings

Navigate to the Insights tab in the repository settings

Use the Audit log section in the organization's GitHub settings

Use the Code tab in the GitHub repository

Answer

Explanation

Audit log events for GitHub Copilot Business can be accessed through the Audit log section within the organization's GitHub settings. This log provides a record of activities related to Copilot usage and configuration.

[Reference: GitHub Copilot Business documentation on audit logs., ]

Questions # 32:

In what ways can GitHub Copilot support a developer during the code refactoring process? (Each correct answer presents part of the solution. Choose two.)

Options:

By offering code transformation examples that enhance performance and reduce complexity.

By independently ensuring compliance with regulatory standards across industries.

By providing suggestions for improving code readability and maintainability based on best practices.

By autonomously refactoring entire codebases to the latest programming language.

Answer

A, C

Explanation

Exact extracts:

“Copilot can propose code transformations that improve performance and reduce complexity.”

[References: GitHub Copilot code refactoring documentation., ===========, ]

Questions # 33:

How does GitHub Copilot identify matching code and ensure that public code is appropriately handled or blocked? (Each correct answer presents part of the solution. Choose two.)

Options:

Using machine learning models trained only on private repositories

Reviewing and storing user-specific private repository data for future suggestions

Filtering out suggestions that match code from public repositories

Implementing safeguards to detect and avoid suggesting verbatim snippets from public code

Answer

C, D

Explanation

Exact extracts:

“GitHub Copilot has a filter to detect code suggestions that match public code on GitHub. When this filter is enabled, Copilot checks suggestions with about 150 characters or more against public code and blocks them if a match is found.”

[References: GitHub Copilot duplication detection and safeguards documentation., ===========, ]

Questions # 34:

Select a strategy to increase the performance of GitHub Copilot Chat.

Options:

Optimize the usage of memory-intensive operations within generated code

Apply prompt engineering techniques to be more specific

Use a single GitHub Copilot Chat query to find resolutions for the collection of technical requirements

Limit the number of concurrent users accessing GitHub Copilot Chat

Answer

Explanation

“Performance of Copilot Chat can be improved with prompt engineering. More specific prompts give more relevant and accurate answers.”

This confirms that applying prompt engineering techniques is the valid strategy.

[References: GitHub Copilot Chat best practices documentation., ===========, ]

Questions # 35:

What is the primary role of the /optimize slash command in Visual Studio?

Options:

Translates code into a more performant language.

Enhances the performance of the selected code by analyzing its runtime complexity.

Automatically formats the code according to the selected style guide.

Summarizes your documentation into more maintainable and readable formats.

Answer

Explanation

“/optimize Analyze and improve running time of the selected code.” This statement from Visual Studio Copilot Chat slash command documentation shows that the role of /optimize is specifically to analyze and improve the runtime performance of selected code, aligning directly with option B.

[References: GitHub Copilot official documentation and Visual Studio Copilot Chat command reference., ===========, ]

Questions # 36:

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.)

Options:

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.

Answer

B, D

Explanation

Exact extracts:

“You can give Copilot Chat additional context using variables such as @workspace or @file to scope the conversation.”

[References: GitHub Copilot Chat variables and context documentation., ===========, ]

Questions # 37:

What method can a developer use to generate sample data with GitHub Copilot? (Each correct answer presents part of the solution. Choose two.)

Options:

Utilizing GitHub Copilot's ability to create fictitious information from patterns in training data.

Leveraging GitHub Copilot's ability to independently initiate and manage data storage services.

Utilize GitHub Copilot's capability to directly access and use databases to create sample data.

Leveraging GitHub Copilot's suggestions to create data based on API documentation in the repository.

Answer

A, D

Explanation

GitHub Copilot can generate sample data by creating fictitious information based on patterns in its training data and by using suggestions based on API documentation within the repository.

[Reference: GitHub Copilot documentation on data generation assistance., ]

Questions # 38:

How does GitHub Copilot Chat ensure that a function works correctly?

Options:

By suggesting assertions based on the code's context and semantics.

By automatically writing all the tests for the function.

By writing the implementation code for the function.

By executing the test cases to validate the correctness of the code.

Answer

Explanation

GitHub Copilot Chat can suggest assertions based on the code's context and semantics to help developers verify the correctness of their functions. These assertions serve as checks that the function behaves as expected under various conditions.

[Reference: GitHub Copilot documentation on testing and code verification., ]

Questions # 39:

How does GitHub Copilot Chat utilize its training data and external sources to generate responses when answering coding questions?

Options:

It primarily relies on the model's training data to generate responses.

It primarily uses search results from Bing to generate responses.

It combines its training data set, code in user repositories, and external sources like Bing to generate responses.

It uses user-provided documentation exclusively to generate responses.

Answer

Explanation

GitHub Copilot Chat combines its training data, code from user repositories, and external sources like Bing to generate comprehensive and relevant responses to coding questions.

[Reference: GitHub Copilot Chat documentation on data sources., ]

Questions # 40:

What are the additional checks that need to pass before the GitHub Copilot responses are submitted to the user? (Each correct answer presents part of the solution. Choose two.)