First, explain the purpose of the 'pick dasher' module and the role of the constructor and adjustKey() method. Then, for each bug, describe the symptom, trace it to the root cause (e.g., missing initialization or incorrect boundary condition), and propose a concrete fix with code or pseudocode. Finally, discuss how you would test the fixes to prevent regressions.
Pro tip: Demonstrate a systematic debugging approach: start by reproducing the bug, then isolate the faulty code, and finally verify the fix with edge cases. This shows maturity and reduces the risk of overlooking related issues.
Briefly explain what the 'pick dasher' module does and the responsibilities of the constructor and adjustKey() method. This sets the context for the bugs.
Identify the missing or incomplete constructor by looking for uninitialized fields or missing setup logic. Explain how this leads to incorrect behavior, such as null pointer exceptions or default values.
Examine the adjustKey() method for boundary conditions, such as loop bounds or index calculations. Determine where the off-by-one occurs and how it affects key adjustment.
Provide clear, concise fixes: for the constructor, add the missing initialization; for adjustKey(), correct the boundary condition (e.g., change < to <= or adjust index). Include code snippets if possible.
Outline how you would test the fixes, including unit tests for edge cases and integration tests to ensure the module works as expected.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
I wrote the happy path first which was fine.
Start by clarifying the two fixes and the off-by-one edge case, then design test cases that directly target the boundary condition and a normal happy path. Structure your answer by explaining each test case's purpose, expected outcome, and how it validates the fix.
Pro tip: Mention that you would also add a regression test for the off-by-one to prevent future reintroduction, and consider property-based testing for broader coverage.
Restate the two fixes and the specific off-by-one scenario to ensure you understand what needs validation. Identify the exact input that triggers the off-by-one (e.g., boundary index, empty input, or maximum value).
Create a test that uses the boundary input that previously caused the off-by-one error. Specify the expected output after the fix and explain why this test would fail without the fix.
Create a simple, typical input that exercises the core functionality. Assert that the output matches the expected correct behavior, ensuring the fix didn't break normal operation.
Think about other potential edge cases related to the fixes (e.g., empty input, single element, negative values) and decide if they are worth adding. Prioritize the required off-by-one and happy path first.
Describe how you would run the tests, interpret failures, and confirm the fixes work. Mention any test framework or tools you'd use and how you'd ensure the tests are reliable.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by framing the code as a critical service that assigns orders to dashers, then systematically address each area: input validation, logging/observability, error handling for no dashers, thread-safety, and unit tests. For each, explain the specific changes you'd make and the trade-offs, tying them back to production reliability and scalability.
Pro tip: Emphasize idempotency and graceful degradation—e.g., when no dashers are available, return a clear error and trigger a retry/backoff mechanism rather than failing silently. Also, mention that you'd add metrics and alerts for key failure modes to enable proactive monitoring.
Ask about expected load, latency SLAs, and consistency requirements to tailor your changes. This shows you think about production context before diving into code.
Validate all inputs (e.g., order ID, dasher ID, location) at the API boundary, reject malformed requests with clear errors, and sanitize data to prevent injection attacks.
Implement structured logging with correlation IDs, and emit metrics (e.g., pick success rate, latency) and traces to monitor the assignment process end-to-end.
For no dashers, return a specific error and enqueue for retry with exponential backoff; for concurrent picks, use optimistic locking or a queue to ensure thread-safety and prevent double-assignment.
Write tests for edge cases: invalid inputs, no dashers, concurrent pick attempts, and failure injection. Use mocks for external dependencies and aim for high coverage of critical paths.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.