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GitHub GitHub-Copilot - GitHub CopilotCertification Exam

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Total 65 questions

How does GitHub Copilot suggest code optimizations for improved performance?

A.

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

B.

By automatically rewriting the codebase to use more efficient code.

C.

By enforcing strict coding standards that ensure optimal performance.

D.

By providing detailed reports on the performance of the codebase.

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

A.

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

B.

It primarily uses search results from Bing to generate responses.

C.

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

D.

It uses user-provided documentation exclusively to generate responses.

What method can be used to interact with GitHub Copilot?

A.

By using a properly configured GitHub CLI

B.

By using chat capabilities in NeoVim

C.

From a watch window in an IDE debug session

D.

From a web browser at https://github.copilot.com

Which of the following scenarios best describes the intended use of GitHub Copilot Chat as a tool?

A.

A complete replacement for developers generating code.

B.

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

C.

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

D.

A tool solely designed for debugging and error correction.

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

A.

Monthly as a subscription

B.

Annually as a subscription

C.

Monthly, as a metered service based on actual consumption

D.

Free (not billed) for all open source projects

How does GitHub Copilot Enterprise assist in code reviews during the pull request process? (Select two.)

A.

It automatically merges pull requests after an automated review.

B.

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

C.

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

D.

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

What is a key consideration when relying on GitHub Copilot Chat's explanations of code functionality and proposed improvements?

A.

The explanations are dynamically updated based on user feedback.

B.

Reviewing and validating the generated output for accuracy and completeness.

C.

GitHub Copilot Chat uses a static database for generating explanations.

D.

The explanations are primarily derived from user-provided documentation.

What role does chat history play in GitHub Copilot's code suggestions?

A.

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

B.

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

C.

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

D.

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

What are the potential limitations of GitHub Copilot Chat? (Each correct answer presents part of the solution. Choose two.)

A.

Limited training data

B.

Ability to handle complex code structures

C.

No biases in code suggestions

D.

Extensive support for all programming languages

How can GitHub Copilot be limited when it comes to suggesting unit tests?

A.

GitHub Copilot can generate all types of unit tests, including those for edge cases and complex integration scenarios.

B.

GitHub Copilot primarily suggests basic unit tests that focus on core functionalities, often requiring additional input from developers for comprehensive coverage.

C.

GitHub Copilot can handle any complexity in code and automatically generate appropriate unit tests.

D.

GitHub Copilot's limitations in generating unit tests can vary based on the IDE version you are using.