The spec was short but I still managed to overthink the input validation part.
Start by restating the spec and explicitly listing your assumptions about inputs, outputs, and edge cases. Then walk through the implementation using clear if/else branches for validation and core logic, explaining why each branch exists. Finally, discuss trade-offs of your approach and how you would test it.
Pro tip: Before writing code, ask clarifying questions about ambiguous requirements and state your assumptions out loud—this shows you think like a senior engineer who prevents bugs before they happen.
Restate the spec in your own words and explicitly list assumptions about input types, ranges, nullability, and expected behavior for edge cases.
Outline the input validation checks using if/else, covering nulls, empty values, out-of-range numbers, and invalid formats. Explain the order of checks and why.
Write the main logic using nested or sequential if/else branches, ensuring each branch handles a specific case and returns a clear result or error.
Explain why you chose if/else over other control flow, and mention potential edge cases you considered and how your code handles them.
Describe how you would test the implementation, including unit tests for validation, core logic, and edge cases, and mention any manual testing.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This part tripped me up more than I expected.
Start by clarifying the new requirement and its assumptions with the interviewer, then outline how you would extend the existing class while considering trade-offs. Focus on demonstrating adaptability, clean design, and the ability to make informed decisions under ambiguity.
Pro tip: Proactively state your assumptions and ask targeted questions to uncover hidden constraints, showing you can navigate ambiguity without over-engineering. Emphasize how your extension maintains backward compatibility and testability.
Ask specific questions to understand the new requirement's scope, constraints, and expected behavior. Confirm assumptions about inputs, outputs, edge cases, and non-functional aspects like performance.
Analyze how the new requirement affects the current class design, including potential changes to interfaces, data structures, and dependencies. Identify risks and areas for refactoring.
Outline one or more approaches to extend the class, such as subclassing, composition, or modifying the class directly. Discuss trade-offs between flexibility, complexity, and maintainability.
Describe how you would implement the chosen approach, including code structure and testing strategy. Highlight how you would ensure correctness and handle edge cases.
Explain how you would review the solution with the interviewer, seek feedback, and iterate if needed. Mention any follow-up considerations like scalability or future extensibility.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
I defaulted to happy path first which is probably the wrong order for a class with this much validation logic.
Start by clarifying the two parts of the implementation and the expected behavior, then outline a test plan that covers happy paths, edge cases, and error handling for each part. Use a testing framework like JUnit or pytest, and structure tests with clear naming and assertions. Finally, discuss how you would run and maintain the tests, including mocking dependencies and measuring coverage.
Pro tip: Emphasize test readability and maintainability by using descriptive test names and the Arrange-Act-Assert pattern. Also, mention that you prioritize testing critical paths and edge cases over achieving 100% coverage, as it demonstrates practical judgment.
Ask questions to understand what the two parts do, their inputs/outputs, and any constraints. Identify the expected behavior for happy paths, edge cases, and error conditions.
For each part, list test scenarios: typical inputs (happy path), boundary values (edge cases), and invalid inputs or failure conditions (error handling). Consider both parts independently and their integration if applicable.
Select an appropriate testing framework (e.g., JUnit, pytest) and decide on mocking strategies for dependencies. Organize tests into logical groups, possibly using describe/it blocks or test classes.
Implement the tests using clear assertions and the Arrange-Act-Assert pattern. Run the tests, ensure they pass, and iterate as needed. Discuss how you would handle flaky tests or slow tests.
Analyze coverage reports to identify untested paths, but prioritize critical scenarios. Discuss how you would maintain tests over time and integrate them into CI/CD.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.