Microsoft GitHub Copilot (GH-300) Certification Sample Questions
The purpose of this Sample Question Set is to provide you with information about the Microsoft GitHub Copilot exam. These sample questions will make you very familiar with both the type and the difficulty level of the questions on the GH-300 certification test. To get familiar with real exam environment, we suggest you try our Sample Microsoft GitHub Copilot Certification Practice Exam. This sample practice exam gives you the feeling of reality and is a clue to the questions asked in the actual Microsoft GitHub Copilot certification exam.
These sample questions are simple and basic questions that represent likeness to the real Microsoft GH-300 exam questions. To assess your readiness and performance with real time scenario based questions, we suggest you prepare with our Premium Microsoft GitHub Copilot Certification Practice Exam. When you solve real time scenario based questions practically, you come across many difficulties that give you an opportunity to improve.
Microsoft GH-300 Sample Questions:
01. Midway through a long GitHub Copilot Chat thread, you asked for an approach based on a caching library that you later decided against. Later answers keep reintroducing that library. You want to keep the rest of the thread. What should you do?
a) Start a new conversation thread and continue the work there
b) Regenerate the most recent response
c) Delete the earlier request about the caching library from the thread
d) Keep asking in the same thread and rephrase each prompt until the library stops appearing
02. Reference Scenario: click here
You need to verify the converted CALC-NET-PAY method before it is merged. Which two actions should you perform?
Each correct answer presents part of the solution.
a) Ask java-converter to confirm that the method is equivalent to the COBOL paragraph, and merge it if the agent agrees
b) Merge the method, because the unit tests that Copilot generated for it already pass
c) Convert the paragraph a second time, and merge the method if both conversions produce identical Java code
d) Run the method on the 4,200 records in tests/regression, and compare each net pay with the COBOL output
e) Review the method's arithmetic against the fixed-point field definitions and ROUNDED phrases in PAYCALC.cbl
03. GitHub Copilot has filters that block or notify users about insecure code patterns detected in its suggestions. Which kinds of pattern are these filters designed to target?
a) Secrets that were committed earlier and remain in the repository's history
b) Hardcoded credentials, SQL injections and path injections
c) Code that matches a public repository
d) Dependency versions that have published security advisories against them
04. Your organization allows suggestions that match public code, and developers use the resulting code references to decide on attribution. Which two limitations of code referencing should the developers understand?
Each correct answer presents a complete solution.
a) Newly committed public code may be missed, because the search index is refreshed every few months
b) Matches are reported only when the public code carries a recognized open source license
c) Code you write yourself, and suggestions you alter before accepting, are not checked for matches
d) Matches in the organization's private repositories are shown only to that organization's members
05. Copilot has stopped using several files in one of your organization's repositories as context, and you suspect that someone edited the content exclusion rules. You need to find who made the most recent change and see the exclusion paths as they were saved. What should you do?
a) Check the security log in your own personal account settings
b) Open the Copilot usage metrics dashboard for the organization and filter it by repository and date
c) Review the commit history of .github/copilot-instructions.md in the repository
d) Select the last-change time on the Copilot settings page to open its audit log entries
06. Reference Scenario: click here
The setup steps workflow for fleet-api has been corrected, and the project's dependencies now install from pkgs.litware.com before each session starts. During a later session, Copilot cloud agent runs npm install @litware/geo-utils to add another internal package, and it reports that the firewall blocked its request to pkgs.litware.com.
You need to allow the agent to install the package. The solution must meet the security requirements. What should you do?
a) Store the registry token as an Agents secret for fleet-api whose name begins with COPILOT_MCP_
b) Add pkgs.litware.com as a domain entry in the custom allowlist under the Copilot settings of fleet-api
c) Register pkgs.litware.com as a server in the MCP configuration of fleet-api
d) Disable the integrated firewall for fleet-api, because the setup steps already reach the registry
07. A contributor with write access opens an issue and assigns it to Copilot cloud agent. The visible text asks for a logging fix. The issue body also contains an HTML comment instructing Copilot to copy the repository's environment variables into the pull request description. How is the HTML comment handled?
a) It reaches the agent, because only comments from users without write access are withheld
b) It reaches the agent, but the agent's firewall blocks the instruction because it came from a comment
c) It is filtered out before the agent receives the issue, so Copilot never sees the instruction
d) It reaches the agent, and Copilot code review strips the instruction from the final pull request
08. Two developers in the same organization send an identical prompt to GitHub Copilot Chat, with the same file open and the same settings. They receive different code in response. What explains the difference?
a) The model is non-deterministic, so repeated runs can produce different outputs
b) Identical prompts always return identical output, so one developer's file must differ
c) Copilot varies its output between users so that no two developers commit the same code
d) One response came from web search instead of the model
09. In Visual Studio Code, a function in auth.js is still highlighted from an earlier task. You open Copilot Chat and ask why the retry logic gives up after one attempt. The retry logic is in a different file, and the answer discusses only the highlighted function. What explains the response?
a) The chat history from the earlier task was sent to the model in place of the new prompt
b) Selected code is removed from the context, so Copilot fell back to guessing from the file name
c) Chat always searches the entire codebase, and it ranked the selected function highest
d) By default, Chat referenced the code you had selected, so the prompt's context held the wrong code
10. Reference Scenario: click here
An engineer opens src/forecast/dedupe.py in Visual Studio Code, with no other files open, and enters /tests in Copilot Chat. The generated tests are written as unittest classes, and none of them passes an empty input or a pair of duplicate keys. You need to regenerate the tests so that they meet the testing requirements.
Which two actions should you perform?
Each correct answer presents part of the solution.
a) Enter /tests again with the same file open and nothing else changed, because each run generates a different set of tests
b) Open an existing test file from the tests folder in an adjacent editor tab before prompting again
c) Accept the generated tests if they pass, because passing tests show that the function's behavior is covered
d) Ask Copilot for tests that cover edge cases, and name empty input and duplicate keys in the prompt
e) Close dedupe.py so that Copilot bases the tests on the whole repository instead of one file
Answers:
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Question: 01 Answer: c |
Question: 02 Answer: d, e |
Question: 03 Answer: b |
Question: 04 Answer: a, c |
Question: 05 Answer: d |
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Question: 06 Answer: b |
Question: 07 Answer: c |
Question: 08 Answer: a |
Question: 09 Answer: d |
Question: 10 Answer: b, d |
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