1. Service Implementation with Smart Integration Tests Goal: Implement a simple service that greets a user by name, with robust integration test coverage. Requirements: A REST endpoint that returns "Hello, !" Name can be received either as: Path variable (e.g., /hello/John) Or query parameter (e.g., /hello?name=John) If the name is missing, return an appropriate error (400 Bad Request) Write integration tests that: Generate dynamic names (e.g., using UUID/random names) Test both input methods (path/query) Ensure the response is correct even when name is missing 2. Add Time-Based Blocking Logic (Smartly Testable) Goal: Add a rule to block the service between 14:00 and 16:00, in a way that can be mocked and tested reliably. ✅ Requirements: When the request comes between 14:00–16:00 → return 503 Service Unavailable Do NOT use LocalTime.now() directly inside logic. Instead: Abstract time-checking logic into a TimeGatekeeper interface with a method like boolean isAllowedNow() Implement a default version that checks current time In tests: Mock the TimeGatekeeper to simulate allowed/blocked times Ensure greeting still works in tests (time-blocking shouldn’t interfere with unrelated test logic) and you shold not mock the clock ✅ Also: Write a unit test for TimeGatekeeper itself Integration tests should pass even if current system time is in blocked range 3. System Design Question: OCR Over Millions of Images in S3 Scenario: You have: A large S3 bucket s3://images-a with millions of images (4–5MB each) A single machine with limited memory, CPU, and disk Goal: Run OCR on all images and save results to a second bucket s3://images-b Constraints: Maximize throughput, support failure recovery, and enable monitoring

the question was to design the system collecting data from different resources downloading .csv files and providing an answer to the user combining all the row data by name and address. It should return the answer within a few seconds