GH-300 GitHub Copilot Exam Questions and Answers

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

To help protect against IP infringement, you need to configure GitHub Copilot to block suggestions that match public code. This ensures that the generated code is not directly copied from publicly available sources.

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.

When the public code filter is enabled, GitHub Copilot runs code suggestions through filters designed to detect matches with publicly available code. This helps prevent the generation of code that might infringe on copyright or licensing agreements.

The duplication detection filter can be configured at the organization level to prevent GitHub Copilot from suggesting publicly available code snippets.

GitHub Copilot Chat helps in understanding existing codebases by answering questions about the code and generating explanations. This allows developers to quickly grasp the functionality and structure of unfamiliar code.

“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.

“GitHub Copilot Individual subscriptions are billed using the payment method configured in your GitHub user profile.”

There is no free tier for open source projects, so option A is correct.

“On GitHub Mobile, you can use emojis in the Copilot Chat interface to provide quick feedback on the responses.”

This makes option A correct.

“/fix: Propose changes to resolve detected issues, such as syntax errors or common programming mistakes, in the selected code.”

This confirms that the /fix command is used to suggest corrections for identified problems.

“Minimizing bias requires diverse datasets, use of fairness metrics, and human oversight throughout development and deployment.”

This clearly confirms that the proper approach is a combination of diverse data, fairness metrics, and oversight.

“Enterprise administrators can configure content exclusions to exclude entire repositories, folders, or specific files from being used by Copilot.”

This confirms that files, folders, and repositories can be excluded, but not individual lines or gists.

While GitHub Copilot Chat can provide helpful explanations and suggestions, it's crucial to review and validate the generated output. Copilot's suggestions are based on its training data, and they may not always be perfectly accurate or complete. Human judgment is essential to ensure the quality and correctness of the code.

GitHub Copilot is an AI-powered code completion tool that integrates directly into supported Integrated Development Environments (IDEs) and code editors, such as Visual Studio Code, JetBrains IDEs, NeoVim, and others. Developers interact with it through their coding environment, where it provides real-time code suggestions, autocompletions, and (in some cases) chat-like capabilities via extensions or plugins (e.g., GitHub Copilot Chat in supported editors).

Evaluation of Options:

A. By using a properly configured GitHub CLIThe GitHub CLI (Command Line Interface) is a tool for interacting with GitHub repositories and workflows from the terminal, but it is not a method for interacting with GitHub Copilot. Copilot operates within code editors/IDEs, not through the CLI.Incorrect.

B. By using chat capabilities in NeoVimThis is partially correct. GitHub Copilot can be used in NeoVim with the appropriate plugin (e.g., the Copilot.vim plugin), and GitHub Copilot Chat—a feature that allows conversational interaction—may also be available depending on the setup and version. However, "chat capabilities in NeoVim" alone is not the primary or standard way to describe Copilot interaction, as it’s more about code suggestions than chat. This is the closest option but not perfectly precise.Partially correct.

C. From a watch window in an IDE debug sessionThe "watch window" in an IDE is used during debugging to monitor variable values, not to interact with GitHub Copilot. Copilot provides suggestions while coding, not specifically in debug sessions or watch windows.Incorrect.

D. From a web browser athttps://github.copilot.comThere is no such URL as "https://github.copilot.com " dedicated to interacting with GitHub Copilot. Copilot is accessed via GitHub’s authentication and integrated into editors/IDEs, not through a standalone web browser interface. Information about Copilot is available on GitHub’s official site (e.g.,https://github.com/features/copilot), but interaction happens in the coding environment.Incorrect.

“The quality of Copilot Chat responses depends on the clarity and specificity of your prompts. You can guide Copilot to follow organizational standards by including examples or requirements in your request.”

This means prompt engineering with specific examples is the way to align with company standards.

Exact extracts:

“GitHub Copilot Chat, like all AI models, is limited by its training data and may not always provide accurate or up-to-date answers.”

“Organization administrators can configure GitHub Copilot Business policies within the organization settings, including restricting usage to certain repositories.”

This proves that the correct way is through organization settings, not repository-level files or GitHub Actions.

The quality of Copilot's suggestions is enhanced by clearly defining the task, using meaningful variable names, and providing examples of the desired output.

“For Copilot Business and Copilot Enterprise, user data such as code suggestions, prompts, and completions are excluded from training GitHub Copilot’s models.”

This confirms that only Business and Enterprise plans provide this exclusion feature.

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.

“When Copilot Chat generates suggestions, it may annotate them with warnings about known insecure patterns, helping developers identify potential vulnerabilities in context.”

This indicates that Copilot Chat assists with security by annotating code suggestions with vulnerability patterns.

Exact extracts:

“When a file is affected by a content exclusion setting, GitHub Copilot will not suggest code completion in that file…”

Exact extracts:

“In supported IDEs, you can ask Copilot Chat to explain code or suggest improvements.”

“Audit logs in Copilot Business allow enterprise and organization administrators to monitor administrator activities and configuration changes.”

This proves that their purpose is not line tracking or license assignment but monitoring admin activities.

“If excluded content is referenced by non-excluded code, such as through function calls, Copilot may still use that reference context.”

This confirms that excluded content can indirectly appear if referenced elsewhere.

“In supported IDEs, you can provide feedback directly from the Copilot Chat panel by selecting the ‘Share Feedback’ option.”

This establishes that the in-IDE “Share Feedback” button is the official channel for submitting user feedback.

The proxy service for GitHub Copilot is hosted on Microsoft Azure.

“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.

“Fairness. AI systems should treat all people fairly.” This principle directly defines fairness as the standard for ensuring equality across all individuals.

“Fill-in-the-Middle (FIM) enables Copilot to consider both prefix and suffix code, generating more accurate suggestions for the missing middle portion.”

This makes option D correct, as it explains how FIM enhances suggestion accuracy.

“GitHub Copilot for Azure DevOps is available to Azure DevOps organizations without requiring a GitHub Enterprise license.”

This confirms that Copilot for Azure DevOps is the correct plan for such organizations.

Exact extracts:

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

Exact extracts:

“The Copilot usage metrics API allows organizations to track the number of suggestions shown and accepted by members.”