Edge Case Handling and Debugging Questions

Covers the systematic identification, analysis, and mitigation of edge cases and failures across code and user flows. Topics include methodically enumerating boundary conditions and unusual inputs such as empty inputs, single elements, large inputs, duplicates, negative numbers, integer overflow, circular structures, and null values; writing defensive code with input validation, null checks, and guard clauses; designing and handling error states including network timeouts, permission denials, and form validation failures; creating clear actionable error messages and informative empty states for users; methodical debugging techniques to trace logic errors, reproduce failing cases, and fix root causes; and testing strategies to validate robustness before submission. Also includes communicating edge case reasoning to interviewers and demonstrating a structured troubleshooting process.

HardSystem Design

0 practiced

Design an observability and test plan to detect and debug partial failures in a distributed transaction that spans services A -> B -> C. Include tracing span design, idempotency and retry semantics, compensating transactions or sagas, and chaos-testing approaches to validate recovery and correctness.

MediumTechnical

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Explain how fuzz testing complements unit and property-based testing. Give a concrete example of a target (e.g., JSON parser, image decoder) where fuzzing likely finds bugs, and describe how you would integrate a fuzzing tool into CI, triage crashes, and manage corpus/seed input growth.

EasyBehavioral

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Tell me about a time when you discovered an important edge case late in a project. Explain how you discovered it, assessed its customer impact and technical risk, implemented a fix, and communicated the change to stakeholders. Follow STAR (Situation, Task, Action, Result).

MediumTechnical

0 practiced

You encounter code that uses sentinel values like -1, null, and empty string to signal different error conditions. Propose a clearer, backward-compatible redesign for error signaling (e.g., result types, exceptions, error objects), and describe a migration plan for callers that minimizes regressions and supports gradual rollout.

HardTechnical

0 practiced

Discuss the trade-offs between strict fail-fast input validation and permissive best-effort parsing in public APIs. Consider security, backward compatibility, client ergonomics, and testability. Give concrete scenarios where strict validation is preferable and where permissive parsing is safer.

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