Test Design from GitHub Scenario | Dataford Interview Questions

Find a real GitHub repository scenario (e.g. a commit where a feature was added or a bug fixed) and use it to design ways to test the AI model.

Asked in the Paid coding training stage. The OP says the search took about an hour using GitHub advanced filters; another commenter suggests checking out the branch prior to a feature or bug fix.

For grading, represent the selected commit as changes, where each item has target, change_type (feature or bugfix), risk from 1 to 5, and input_classes. Implement the function below. Return at most limit change targets, ordered by descending priority, with the test strategies that apply to each target.

Constraints

1 <= len(changes) <= 100
1 <= limit <= len(changes)
Each risk value is an integer from 1 through 5
change_type is either feature or bugfix
input_classes contains unique strings

Function Signature

def prioritize_ai_tests(changes, limit):

Your question is Test Design from GitHub Scenario. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Problem

Find a real GitHub repository scenario (e.g. a commit where a feature was added or a bug fixed) and use it to design ways to test the AI model.

Asked in the Paid coding training stage. The OP says the search took about an hour using GitHub advanced filters; another commenter suggests checking out the branch prior to a feature or bug fix.

Constraints

1 <= len(changes) <= 100
1 <= limit <= len(changes)
Each risk value is an integer from 1 through 5
change_type is either feature or bugfix
input_classes contains unique strings

Function Signature

def prioritize_ai_tests(changes, limit):

Your question is Test Design from GitHub Scenario. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.