GH-300 GitHub Copilot Exam Questions and Answers

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.

GitHub Copilot Individual

GitHub Copilot Business

GitHub Copilot Enterprise

GitHub Copilot Professional

A complete replacement for developers generating code.

A productivity tool that provides suggestions, but relying on human judgment.

A solution for software development, requiring no additional input or oversight.

A tool solely designed for debugging and error correction.

GitHub Copilot Business

GitHub Copilot Codespace

GitHub Copilot Individual

GitHub Copilot Enterprise

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.

Files

Folders

Lines in files

Gists

Repositories

Suggestions matching public code to 'blocked'

Enforce blocking of MIT or GPL licensed code

You need to check code suggestions yourself before accepting

Enable GitHub Copilot license checking

Based on the payment method in your user profile

N/A – Copilot Individual is a free service for all open source projects

Through an invoice or a credit card

Through an Azure Subscription

Chat history is used to train the GitHub Copilot model in real-time.

Chat history provides context to GitHub Copilot, improving the relevance and accuracy of its code suggestions.

Chat history is stored and shared with other users to enhance collaboration.

Chat history is irrelevant to GitHub Copilot and does not affect its functionality.

Accepted chat suggestions

Code suggestions made by GitHub Copilot

Changes to content exclusion settings

Suggestions blocked by duplication detection filtering

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

Inline suggestions

Pull request summaries

Knowledge bases

Chat

GitHub Copilot can automatically handle project management tasks.

GitHub Copilot can completely replace the need for human collaboration.

GitHub Copilot can predict and prevent bugs before they occur.

GitHub Copilot allows developers to stay in their IDE.

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.

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.

Provide specific success criteria

Provide all information about the utilized files

Provide insight on where to get the content from to get a response

Provide links to supporting documentation

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

Describing in your prompt what your role is to get a better suggestion

Tell GitHub Copilot in what tone of voice it should respond

Prompt GitHub Copilot to explain what was the role of a suggestion

Giving GitHub Copilot multiple examples of the form of the data you want to use

Information from the IDE like open tabs, cursor location, selected code.

All the code in the current repository and any git submodules.

The open tabs in the IDE and the current folder of the terminal.

All the code visible in the current IDE.

The Settings menu in the GitHub Mobile app.

The feedback section on the GitHub website.

Use the emojis in the Copilot Chat interface.

By tweeting at GitHub's official X (previously known as Twitter) account.

Generate suggestions

Capturing the user's context

Processing telemetry data

Retraining the model

Storing user data

GitHub Copilot Individuals

GitHub Copilot Business

GitHub Copilot Enterprise

GitHub Copilot Codespace

Restricts Copilot to use only external databases for generating code suggestions.

Allows Copilot to generate suggestions based only on the prefix of the code.

Ignores both the prefix and suffix of the code, focusing only on user comments for context.

Improves suggestions by considering both the prefix and suffix of the code, filling in the middle part more accurately.

Hate speech or discriminatory language (e.g., racial slurs, offensive stereotypes)

Sexually suggestive or explicit content

Code that contains logical errors or produces unexpected results

Code comments containing strong opinions or criticisms

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.

Because GitHub Copilot can cover all possible scenarios in your test cases.

Because GitHub Copilot generates the best code possible for the test scenario.

Because GitHub Copilot's generated test cases may not cover all possible scenarios.

Because GitHub Copilot replaces the need for manual testing.

Fairness

Transparency

Inclusiveness

Accountability

Initiates a code review with static analysis tools for security and logic errors.

Converts pseudocode into executable code, optimizing for readability and maintainability.

Generates new code snippets based on language syntax and best practices.

Proposes changes for detected issues, suggesting corrections for syntax errors and programming mistakes.

Apply policies through the GitHub Actions configuration

Create a copilot.policy file in each repository

Configure the policies in the organization settings

Create a copilot.policy in the .github repository

It automatically merges pull requests after an automated review.

It generates a prose summary and a bulleted list of key changes for pull requests.

It can validate the accuracy of the changes in the pull request.

It can answer questions about the changeset of the pull request.

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."

Suggest innovative coding solutions that are not yet popular.

Suggest completely novel projects, while reducing time on a project.

Suggest code snippets that reflect the most common practices in the training data.

Suggest homogeneous solutions if provided a diverse data set.

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.