GH-300 GitHub Copilot Exam Questions and Answers

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

"Show me how to improve the readability of this function."

"Suggest ways to enhance the maintainability of this code segment."

"Refactor my application to meet the latest coding standards."

"Predict future coding trends and update my codebase accordingly."

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.

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.

Fairness

Transparency

Inclusiveness

Accountability

GitHub Copilot Individual

GitHub Copilot Enterprise

GitHub Copilot for Azure DevOps

Copilot Teams

The default execution confirmation

Usage analytics

The default editor

GitHub CLI subcommands

Generate suggestions

Capturing the user's context

Processing telemetry data

Retraining the model

Storing user data

Files

Folders

Lines in files

Gists

Repositories

Code suggestions are guaranteed to not expose known security vulnerabilities

You can use keyboard shortcuts to accept the next word in a suggestion

Code suggestions are limited to single-line suggestions

Code suggestions will always compile or run without modifications

Alternative code suggestions can be shown in a new tab

Code snippets

Compiled binaries

Documentation

Design patterns

Screenshots

It filters out irrelevant information from the user's input prompt.

It enriches the input prompt with additional context before passing it to the language model.

It directly generates a response based on the user's input prompt.

It formats the output response before presenting it to the user.

GitHub Copilot may introduce security vulnerabilities by suggesting code with known exploits.

GitHub Copilot may decrease developer velocity by requiring too much time in prompt engineering.

GitHub Copilot's suggestions may not always reflect best practices or the latest coding standards.

GitHub Copilot may increase development lead time by providing irrelevant suggestions.

By regularly updating the AI filtering algorithm.

By relying on a well-regarded AI development company.

By focusing on user satisfaction with the content filtering.

By providing clear explanations about the types of content the AI is designed to filter and how it arrives at its conclusion.

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

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.

GitHub Copilot can independently verify the statistical significance of results.

GitHub Copilot's suggestions are based on statistical trends and may not always apply accurately to specific datasets.

GitHub Copilot will automatically correct any statistical errors found in the user's initial code.

GitHub Copilot can design new statistical methods that have not been previously documented.

Responses are faster to produce and appear sooner

Responses use practices and patterns in your repositories

Responses use the organization's LLM engine

Responses are guaranteed to be correct

/init-tests

/create-tests

/generate-tests

/tests

By filling out a feedback form on the GitHub website

By emailing the support team directly

By posting on the GitHub forums

Through the "Share Feedback" button in the Copilot Chat panel

Only giving GitHub Copilot a question as a prompt and no examples

Giving GitHub Copilot examples of the problem you want to solve

Telling GitHub Copilot it needs to show only the correct answer

Giving GitHub Copilot examples of the algorithm and outcome you want to use

Giving as little context to GitHub Copilot as possible

Constructs detailed test documentation.

Creates unit tests for the selected code.

Integrates with external testing frameworks.

Executes test cases to find issues with the code.

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

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.

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

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.

By identifying a pattern in the way you write tests and suggesting similar patterns for future tests.

By automatically fixing all tests in the code based on the context.

By providing documentation references based on industry best practices.

By writing the implementation code for the function based on context.

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.

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.

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.

Blocking public code matches

Blocking license check configuration

Allowing public code matches

Allowing license check configuration

All repos are indexed

Indexing is static

It is an Enterprise feature

All file types are indexed

By analyzing the codebase and suggesting more efficient algorithms or data structures.

By automatically rewriting the codebase to use more efficient code.

By enforcing strict coding standards that ensure optimal performance.

By providing detailed reports on the performance of the codebase.