Latest Microsoft GH-300 Exam questions and answers [Q39-Q55]

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Latest Microsoft GH-300 Exam questions and answers

BraindumpsIT GH-300 Exam Practice Test Questions (Updated 123 Questions)

Microsoft GH-300 Exam Syllabus Topics:

Topic	Details
Topic 1	Domain 6: Testing with GitHub Copilot: This section measures abilities of QA Engineers and Test Automation Specialists to use Copilot for test generation, including unit and integration tests. It explains how Copilot can identify edge cases and assist in writing assertions. The domain also covers different Copilot subscription SKUs, privacy considerations, organizational code suggestion settings, and configuration files related to Copilot.
Topic 2	GitHub Copilot Plans and Feature: This domain targets Product Managers and DevOps Engineers and focuses on understanding the various GitHub Copilot subscription plans like Individual, Business, and Enterprise, including distinctions and management features. It covers how Copilot is integrated into IDEs, different triggering methods for code suggestions, organizational policy management, subscription administration via API, and effective use of Copilot Chat and Knowledge Bases. Candidates also learn about CLI usage and configuration.
Topic 3	Developer Use Cases for AI: Targeting Software Engineers and Technical Leads, this domain elaborates on how AI improves developer productivity across common tasks like learning new languages, translation, documentation, debugging, data science, and refactoring. It discusses Copilot’s support in software development lifecycle management and highlights its limitations. Use of the productivity API to track Copilot’s impact is also included.

NEW QUESTION 39
How can you get multiple suggestions from GitHub Copilot?

By asking for multiple suggestions using comments in your code

By opening the completions panel in your editor

By using the inline chat functionality with the command ‘multiple’

By using @workspace in the chat window

You can get multiple suggestions by opening the completions panel in your editor, which displays alternative code suggestions.

NEW QUESTION 40
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.

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.

NEW QUESTION 41
Which GitHub Copilot plan allows for prompt and suggestion collection?

GitHub Copilot Individuals

GitHub Copilot Business

GitHub Copilot Enterprise

GitHub Copilot Codespace

GitHub Copilot Enterprise allows for prompt and suggestion collection, enabling organizations to analyze and improve their usage of the tool.

NEW QUESTION 42
How does GitHub Copilot assist developers in reducing the amount of manual boilerplate code they write?

By engaging in real-time collaboration with multiple developers to write boilerplate code.

By predicting future coding requirements and pre-emptively generating boilerplate code.

By refactoring the entire codebase to eliminate boilerplate code without developer input.

By suggesting code snippets that can be reused across different parts of the project.

“Copilot helps reduce boilerplate by suggesting reusable code snippets for repetitive structures across your project.” This proves that Copilot saves time by generating reusable snippets, not by preemptively or automatically refactoring entire codebases.
References: GitHub Copilot productivity documentation.

NEW QUESTION 43
What are the effects of content exclusions? (Each correct answer presents part of the solution. Choose two.)

GitHub Copilot suggestions are no longer available in the excluded files.

The excluded content is not directly available to GitHub Copilot to use as context.

The excluded content is no longer used while debugging the code.

The IDE will not count coding suggestions in the excluded content.

Content exclusions prevent GitHub Copilot from using the excluded content as context and stop suggestions from being generated in those files.
Reference: GitHub Copilot content exclusion documentation.

NEW QUESTION 44
Identify the right use cases where GitHub Copilot Chat is most effective. (Each correct answer presents part of the solution. Choose two.)

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

GitHub Copilot Chat is effective for explaining and translating legacy code and generating unit test scenarios for new code.
Reference: GitHub Copilot Chat use cases.

NEW QUESTION 45
What two options navigate to configure duplicate detection? (Each correct answer presents part of the solution. Choose two.)

Enterprise settings # Copilot # Policies

Repository settings # Copilot # Policies

Organization settings # Copilot # Policies

User settings # Copilot # Policies

“Duplicate detection and blocking of public code matches can be configured by enterprise administrators in enterprise or organization-level Copilot policies.” This confirms that enterprise and organization settings are the correct paths.
References: GitHub Copilot policy configuration documentation.

NEW QUESTION 46
How is GitHub Copilot Individual billed? (Each correct answer presents part of the solution. Choose two.)

Monthly as a subscription

Annually as a subscription

Monthly, as a metered service based on actual consumption

Free (not billed) for all open source projects

GitHub Copilot Individual is billed as a monthly or annual subscription.

NEW QUESTION 47
What is the correct way to exclude specific files from being used by GitHub Copilot Business during code suggestions?

Modify the .gitignore file to include the specific files.

Add the specific files to a copilot.ignore file.

Use the GitHub Copilot settings in the user interface to exclude files.

Rename the files to include the suffix _no_copilot.

The correct way to exclude files is through the GitHub Copilot settings in the user interface, which allows administrators to specify files and directories to be ignored.
Reference: GitHub Copilot Business content exclusion documentation.

NEW QUESTION 48
How can the concept of fairness be integrated into the process of operating an AI tool?

Focusing on accessibility will ensure fairness.

Focusing on collecting large datasets for training will ensure fairness.

Regularly monitoring the AI tool’s performance will ensure fairness in its outputs.

Training AI data and algorithms to be free from biases will ensure fairness.

Fairness in AI tools is achieved by training the data and algorithms to be free from biases. This ensures that the tool treats all users equitably and avoids discriminatory outcomes.
Reference: Microsoft’s AI principles and fairness guidelines.

NEW QUESTION 49
How does GitHub Copilot Chat utilize its training data and external sources to generate responses when answering coding questions?

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.

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.

NEW QUESTION 50
What is the main purpose of the duplication detection filter in GitHub Copilot?

To compare user-generated code against a private repository for potential matches.

To allow administrators to control which suggestions are visible to developers based on custom criteria.

To encourage the user to follow coding best practices preventing code duplication.

To detect and block suggestions that match public code snippets on GitHub if they contain about 150 characters.

“GitHub Copilot has a duplication detection filter that checks suggestions of about 150 characters or longer against public code on GitHub. If a match is found, the suggestion is blocked if you have configured blocking.” This clearly defines the purpose as preventing Copilot from suggesting verbatim code found publicly.
References: GitHub Copilot duplication detection documentation.

NEW QUESTION 51
How can you use GitHub Copilot to get inline suggestions for refactoring your code? (Select two.)

By adding comments to your code and triggering a suggestion.

By highlighting the code you want to fix, right-clicking, and selecting “Fix using GitHub Copilot.”

By running the gh copilot fix command.

By using the “/fix” command in GitHub Copilot in-line chat.

By highlighting the code you want to fix, right-clicking, and selecting “Refactor using GitHub Copilot.”

You can use GitHub Copilot for inline refactoring suggestions by adding comments to your code to trigger suggestions and by highlighting the code and selecting “Refactor using GitHub Copilot” from the context menu.
Reference: GitHub Copilot refactoring documentation.

NEW QUESTION 52
What is one of the recommended practices when using GitHub Copilot Chat to enhance code quality?

Avoid using Copilot for complex tasks.

Disable Copilot’s inline suggestions.

Regularly review and refactor the code suggested by Copilot.

Rely solely on Copilot’s suggestions without reviewing them.

“Developers should always review, test, and refactor code generated by GitHub Copilot. Copilot can speed up development, but maintaining code quality requires careful human oversight.” This establishes that regularly reviewing and refactoring Copilot suggestions is the recommended best practice.
References: GitHub Copilot responsible use guidelines.

NEW QUESTION 53
How can you use GitHub Copilot to get inline suggestions for refactoring your code? (Select two.)

By adding comments to your code and triggering a suggestion.

By highlighting the code you want to fix, right-clicking, and selecting “Fix using GitHub Copilot.”

By running the gh copilot fix command.

By using the “/fix” command in GitHub Copilot in-line chat.

By highlighting the code you want to fix, right-clicking, and selecting “Refactor using GitHub Copilot.”

NEW QUESTION 54
When crafting prompts for GitHub Copilot, what is a recommended strategy to enhance the relevance of the generated code?

Keep the prompt as short as possible, using single words or brief phrases.

Write the prompt in natural language without any programming language.

Avoid mentioning the programming language to allow for more flexible suggestions.

Provide examples of expected input and output within the prompt.

“To get the best results from GitHub Copilot, provide clear prompts and, when possible, include examples of expected input and output.” This establishes that including examples is a recommended prompt engineering strategy.
References: GitHub Copilot prompt engineering documentation.

NEW QUESTION 55
How can GitHub Copilot assist developers during the requirements analysis phase of the Software Development Life Cycle (SDLC)?

By automatically generating detailed requirements documents.

By providing templates and code snippets that help in documenting requirements.

By identifying and fixing potential requirement conflicts when using /help.

By managing stakeholder communication and meetings.

GitHub Copilot can assist during the requirements analysis phase by providing templates and code snippets that aid in documenting requirements. This helps streamline the process of capturing and organizing project requirements.

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