[2025年10月24日]GitHub-Copilot問題集完全版問題、試験学習ガイド
GitHub Certification無料認定試験材料PassTestからの68問題
質問 # 36
How can GitHub Copilot be limited when it comes to suggesting unit tests?
- A. GitHub Copilot primarily suggests basic unit tests that focus on core functionalities, often requiring additional input from developers for comprehensive coverage.
- B. GitHub Copilot can generate all types of unit tests, including those for edge cases and complex integration scenarios.
- 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.
正解：A
解説：
GitHub Copilot often suggests basic unit tests and may not cover all edge cases or complex integration scenarios, requiring developers to supplement its suggestions.
質問 # 37
What types of prompts or code snippets might be flagged by the GitHub Copilot toxicity filter? (Each correct answer presents part of the solution. Choose two.)
- A. Hate speech or discriminatory language (e.g., racial slurs, offensive stereotypes)
- B. Code that contains logical errors or produces unexpected results
- C. Code comments containing strong opinions or criticisms
- D. Sexually suggestive or explicit content
正解：A、D
解説：
GitHub Copilot includes a toxicity filter to prevent the generation of harmful or inappropriate content. This filter flags prompts or code snippets that contain hate speech, discriminatory language, or sexually suggestive or explicit content. This ensures a safe and respectful coding environment.
質問 # 38
How long does it take content exclusion to add or be updated?
- A. 60 - 90 minutes
- B. 45 - 60 minutes
- C. 24 hours
- D. Up to 30 minutes
正解：D
解説：
Content exclusions typically take up to 30 minutes to be added or updated.
質問 # 39
Which of the following scenarios best describes the intended use of GitHub Copilot Chat as a tool?
- A. A solution for software development, requiring no additional input or oversight.
- B. A tool solely designed for debugging and error correction.
- C. A complete replacement for developers generating code.
- D. A productivity tool that provides suggestions, but relying on human judgment.
正解：D
解説：
GitHub Copilot Chat is designed to be a productivity enhancer, not a replacement for human developers. It provides suggestions and assists with coding tasks, but the final decision and validation always rest with the developer. Copilot Chat is meant to augment the developer's workflow, making it faster and more efficient, but it does not remove the need for human oversight and judgment.
質問 # 40
What method can be used to interact with GitHub Copilot?
- A. From a watch window in an IDE debug session
- B. By using a properly configured GitHub CLI
- C. By using chat capabilities in NeoVim
- D. From a web browser at https://github.copilot.com
正解：C
解説：
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 allowsconversational 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.
質問 # 41
What practices enhance the quality of suggestions provided by GitHub Copilot? (Select three.)
- A. Including personal information in the code comments
- B. Providing examples of desired output
- C. Using meaningful variable names
- D. Clearly defining the problem or task
- E. Use a .gitignore file to exclude irrelevant files
正解：B、C、D
解説：
The quality of Copilot's suggestions is enhanced by clearly defining the task, using meaningful variable names, and providing examples of the desired output.
質問 # 42
How does GitHub Copilot Chat ensure that a function works correctly?
- A. By automatically writing all the tests for the function.
- B. By executing the test cases to validate the correctness of the code.
- C. By writing the implementation code for the function.
- D. By suggesting assertions based on the code's context and semantics.
正解：D
解説：
GitHub Copilot Chat can suggest assertions based on the code's context and semantics to help developers verify the correctness of their functions. These assertions serve as checks that the function behaves as expected under various conditions.
質問 # 43
How can you improve the context used by GitHub Copilot? (Each correct answer presents part of the solution.
Choose two.)
- A. By adding the full file paths to your prompt of important files
- B. By adding the important files to your .gitconfig
- C. By opening the relevant tabs in your IDE
- D. By adding relevant code snippets to your prompt
正解：C、D
解説：
Improving the context for GitHub Copilot involves opening relevant files in your IDE to provide immediate context and adding relevant code snippets directly to your prompts to give Copilot specific examples and information.
質問 # 44
What is a likely effect of GitHub Copilot being trained on commonly used code patterns?
- A. Suggest homogeneous solutions if provided a diverse data set.
- B. Suggest innovative coding solutions that are not yet popular.
- C. Suggest completely novel projects, while reducing time on a project.
- D. Suggest code snippets that reflect the most common practices in the training data.
正解：D
解説：
GitHub Copilot is likely to suggest code snippets that reflect common practices in its training data, as it learns from frequently used patterns.
質問 # 45
How can the concept of fairness be integrated into the process of operating an AI tool?
- A. Regularly monitoring the AI tool's performance will ensure fairness in its outputs.
- B. Focusing on accessibility will ensure fairness.
- C. Training AI data and algorithms to be free from biases will ensure fairness.
- D. Focusing on collecting large datasets for training will ensure fairness.
正解：C
解説：
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.
質問 # 46
How does GitHub Copilot Chat help in understanding the existing codebase?
- A. By automatically refactoring code to improve readability.
- B. By answering questions about the code and generating explanations.
- C. By running code linters and formatters.
- D. By providing visual diagrams of the code structure.
正解：B
解説：
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.
質問 # 47
What are two techniques that can be used to improve prompts to GitHub Copilot? (Select two.)
- A. Provide insight on where to get the content from to get a response
- B. Provide links to supporting documentation
- C. Provide specific success criteria
- D. Provide all information about the utilized files
正解：B、C
解説：
Improving prompts involves providing specific success criteria and including links to supporting documentation to give GitHub Copilot more context and direction.
質問 # 48
Which principle emphasizes that AI systems should be understandable and provide clear information on how they work?
- A. Inclusiveness
- B. Fairness
- C. Transparency
- D. Accountability
正解：C
解説：
The principle of transparency emphasizes that AI systems should be understandable and provide clear information about their operations. This ensures that users can understand how the AI arrivesat its decisions and suggestions.
質問 # 49
When can GitHub Copilot still use content that was excluded using content exclusion?
- A. When the user prompts with @workspace.
- B. If the content exclusion was configured at the enterprise level, and is overwritten at the organization level.
- C. When the repository level settings allow overrides by the user.
- D. If the contents of an excluded file are referenced in code that is not excluded, for example function calls.
正解：D
解説：
GitHub Copilot can still use excluded content if it is referenced in code that is not excluded, such as function calls.
質問 # 50
How can you use GitHub Copilot to get inline suggestions for refactoring your code? (Select two.)
- A. By highlighting the code you want to fix, right-clicking, and selecting "Fix using GitHub Copilot."
- B. By highlighting the code you want to fix, right-clicking, and selecting "Refactor using GitHub Copilot."
- C. By using the "/fix" command in GitHub Copilot in-line chat.
- D. By adding comments to your code and triggering a suggestion.
- E. By running the gh copilot fix command.
正解：B、D
解説：
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.
質問 # 51
What should developers consider when relying on GitHub Copilot for generating code that involves statistical analysis?
- A. GitHub Copilot's suggestions are based on statistical trends and may not always apply accurately to specific datasets.
- B. GitHub Copilot will automatically correct any statistical errors found in the user's initial code.
- C. GitHub Copilot can design new statistical methods that have not been previously documented.
- D. GitHub Copilot can independently verify the statistical significance of results.
正解：A
解説：
Developers should consider that GitHub Copilot's suggestions are based on statistical trends and may not always be accurate for specific datasets, requiring careful validation.
質問 # 52
What role does chat history play in GitHub Copilot's code suggestions?
- A. Chat history is stored and shared with other users to enhance collaboration.
- B. Chat history is irrelevant to GitHub Copilot and does not affect its functionality.
- C. Chat history provides context to GitHub Copilot, improving the relevance and accuracy of its code suggestions.
- D. Chat history is used to train the GitHub Copilot model in real-time.
正解：C
解説：
Chat history provides valuable context to GitHub Copilot, helping it generate more relevant and accurate code suggestions based on previous interactions and conversations.
質問 # 53
What is a key consideration when relying on GitHub Copilot Chat's explanations of code functionality and proposed improvements?
- A. GitHub Copilot Chat uses a static database for generating explanations.
- B. The explanations are primarily derived from user-provided documentation.
- C. The explanations are dynamically updated based on user feedback.
- D. Reviewing and validating the generated output for accuracy and completeness.
正解：D
解説：
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.
質問 # 54
How do you generate code suggestions with GitHub Copilot in the CLI?
- A. Use copilot suggest -> Write the command you want -> Select the best suggestion from the list.
- B. Type out the code snippet -> Use the copilot refine command to enhance it -> Review the suggested command.
- C. Describe the project's architecture -> Use the copilot generate command -> Accept the generated suggestion.
- D. Write code comments -> Press the suggestion shortcut -> Select the best suggestion from the list.
正解：D
解説：
In the CLI, GitHub Copilot generates code suggestions by analyzing code comments. You write comments describing what you want, and Copilot provides relevant code suggestions. You then select the best suggestion from the list.
質問 # 55
Which of the following GitHub Copilot Business related activities can be tracked using the organization audit logs?
- A. Changes to content exclusion settings
- B. Suggestions blocked by duplication detection filtering
- C. Accepted chat suggestions
- D. Code suggestions made by GitHub Copilot
正解：A
解説：
Organization audit logs track changes to content exclusion settings, providing administrators with visibility into configuration changes.
質問 # 56
What is a benefit of using custom models in GitHub Copilot?
- A. Responses are guaranteed to be correct
- B. Responses use the organization's LLM engine
- C. Responses are faster to produce and appear sooner
- D. Responses use practices and patterns in your repositories
正解：D
解説：
Custom models in GitHub Copilot allow the tool to learn from the specific code patterns and practices within your repositories. This results in suggestions that are more aligned with your organization's coding standards and conventions, improving the relevance and accuracy of the generated code.
質問 # 57
In what way can GitHub Copilot and GitHub Copilot Chat aid developers in modernizing applications?
- A. GitHub Copilot can directly convert legacy applications into cloud-native architectures.
- B. GitHub Copilot can create and deploy full-stack applications based on a single query.
- C. GitHub Copilot can refactor applications to align with upcoming standards.
- D. GitHub Copilot can suggest modern programming patterns based on your code.
正解：D
解説：
GitHub Copilot and GitHub Copilot Chat are powerful AI-driven tools designed to assist developers by providing context-aware code suggestions and interactive support. Specifically, in the context of modernizing applications, GitHub Copilot excels at analyzing existing code and suggesting modern programming patterns, best practices, and syntax improvements that align with contemporary development standards. For example, it can recommend updates to outdated constructs, propose more efficient algorithms, or suggest frameworks and libraries that are widely used in modern application development.
* Why not A?GitHub Copilot does not "directly convert" legacy applications into cloud-native architectures. It can assist by suggesting code changes or patterns that support such a transition, but it doesn't autonomously perform the full conversion process, which involves architectural decisions and deployment steps beyond its scope.
* Why not C?While GitHub Copilot can generate code snippets and even larger portions of an application, it cannot create and deploy full-stack applications from a single query. It requires developer input, refinement, and integration to achieve a complete, deployable solution.
* Why not D?GitHub Copilot can assist with refactoring by suggesting improvements to existing code, but it doesn't inherently "align with upcoming standards" in a predictive sense. Its suggestions are based on current best practices and the data it was trained on, not future standards that are yet to be defined.
Thus,Bis the most accurate and realistic way GitHub Copilot aids developers in modernizing applications, leveraging its ability to provide relevant, context-based suggestions to update and improve codebases.
質問 # 58
How does GitHub Copilot suggest code optimizations for improved performance?
- A. By providing detailed reports on the performance of the codebase.
- B. By analyzing the codebase and suggesting more efficient algorithms or data structures.
- C. By enforcing strict coding standards that ensure optimal performance.
- D. By automatically rewriting the codebase to use more efficient code.
正解：B
解説：
GitHub Copilot suggests code optimizations by analyzing the codebase and recommending more efficient algorithms or data structures.
質問 # 59
How can you get multiple suggestions from GitHub Copilot?
- A. By opening the completions panel in your editor
- B. By using @workspace in the chat window
- C. By asking for multiple suggestions using comments in your code
- D. By using the inline chat functionality with the command 'multiple'
正解：A
解説：
You can get multiple suggestions by opening the completions panel in your editor, which displays alternative code suggestions.
質問 # 60
Which of the following is a risk associated with using AI?
- A. AI algorithms are incapable of perpetuating existing biases.
- B. AI systems can sometimes make decisions that are difficult to interpret.
- C. AI replaces the need for developer opportunities in most fields.
- D. AI eliminates the need for data privacy regulations.
正解：B
解説：
A risk associated with AI is that its decisions can be difficult to interpret, leading to a lack of transparency and potential misunderstandings.
質問 # 61
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GitHub-Copilot試験の問題集簡単まとめ：https://www.passtest.jp/GitHub/GitHub-Copilot-shiken.html
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