Start by clarifying the problem and constraints, then define the DP state and recurrence relation. Implement the solution efficiently, test with examples, and optimize space if possible.
Pro tip: Communicate your thought process clearly and manage your time by tackling the highest-value parts first. If stuck, start with a brute-force solution and then optimize.
Restate the problem in your own words, ask clarifying questions, and identify input/output and constraints.
Determine what the state represents and how it transitions from smaller subproblems. Write down the recurrence relation.
Code the DP solution, starting with a recursive memoized approach if easier, then convert to iterative if needed. Test with provided examples and edge cases.
Analyze time and space complexity. Consider space optimization techniques like rolling arrays or state compression.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the requirements and test cases to understand the expected behavior and constraints. Then design a minimal Spring Boot application that satisfies the tests, focusing on clean API design and integration points. Implement iteratively, running tests frequently to ensure correctness and address edge cases.
Pro tip: Before writing any code, read the test cases carefully to infer the exact API contract and error handling expectations; this saves time and ensures you meet all requirements. Also, consider non-functional aspects like logging and validation early, as they often appear in Amazon's leadership principles.
Ask questions to understand the feature scope, expected inputs/outputs, and any constraints. Review the provided test cases to deduce the API endpoints, request/response formats, and error scenarios.
Sketch a high-level design: identify necessary Spring Boot components (controllers, services, repositories), data models, and integration points. Consider trade-offs between simplicity and extensibility.
Set up the Spring Boot project with required dependencies. Implement one endpoint or feature at a time, running the relevant tests after each change to validate progress.
Ensure robust error handling (e.g., validation, exceptions) and cover edge cases like empty inputs, invalid data, or concurrent access. Add logging for observability.
Once all tests pass, refactor code for readability and maintainability. Run the full test suite to confirm everything works, and consider performance implications.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.