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GitHub CopilotCertification Exam Sample Questions (Q58-Q63):
NEW QUESTION # 58
How can GitHub Copilot assist developers during the requirements analysis phase of the Software Development Life Cycle (SDLC)?
- A. By automatically generating detailed requirements documents.
- B. By managing stakeholder communication and meetings.
- C. By identifying and fixing potential requirement conflicts when using /help.
- D. By providing templates and code snippets that help in documenting requirements.
Answer: D
Explanation:
GitHub Copilot can assist during the requirements analysis phase by providing templates and code snippets that aid in documenting requirements. This helps streamline the process of capturing and organizing project requirements.
NEW QUESTION # 59
How does GitHub Copilot Chat utilize its training data and external sources to generate responses when answering coding questions?
- A. It combines its training data set, code in user repositories, and external sources like Bing to generate responses.
- B. It primarily uses search results from Bing to generate responses.
- C. It primarily relies on the model's training data to generate responses.
- D. It uses user-provided documentation exclusively to generate responses.
Answer: A
Explanation:
GitHub Copilot Chat combines its training data, code from user repositories, and external sources like Bing to generate comprehensive and relevant responses to coding questions.
NEW QUESTION # 60
Why is code reviewing still necessary when using GitHub Copilot to write tests?
- A. Because GitHub Copilot generates the best code possible for the test scenario.
- B. Because GitHub Copilot replaces the need for manual testing.
- C. Because GitHub Copilot's generated test cases may not cover all possible scenarios.
- D. Because GitHub Copilot can cover all possible scenarios in your test cases.
Answer: C
Explanation:
Code review is necessary because GitHub Copilot's generated test cases might not cover all possible scenarios, especially edge cases and complex interactions.
NEW QUESTION # 61
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. Code that contains logical errors or produces unexpected results
- B. Hate speech or discriminatory language (e.g., racial slurs, offensive stereotypes)
- C. Code comments containing strong opinions or criticisms
- D. Sexually suggestive or explicit content
Answer: B,D
Explanation:
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.
NEW QUESTION # 62
What should developers consider when relying on GitHub Copilot for generating code that involves statistical analysis?
- A. GitHub Copilot can design new statistical methods that have not been previously documented.
- B. GitHub Copilot will automatically correct any statistical errors found in the user's initial code.
- C. GitHub Copilot's suggestions are based on statistical trends and may not always apply accurately to specific datasets.
- D. GitHub Copilot can independently verify the statistical significance of results.
Answer: C
Explanation:
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.
NEW QUESTION # 63
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