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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.

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
You inherit a monolithic codebase with inconsistent error-handling: many functions return special sentinel values, inconsistent error codes, and sparse logging. Outline an incremental migration plan to a consistent error-handling model (e.g., typed errors or centralized error objects), how to test each migration step, and how to avoid regressions while keeping teams productive.
HardTechnical
0 practiced
Design a CI pipeline that catches subtle edge cases before merge. Components to consider: flakiness detection, integration with fuzzing, sanitizer runs (ASAN/TSAN/UBSAN), performance regression detection, cross-language contract tests, and nightly heavy tests. Describe stage ordering, resource isolation, and strategies to keep developer feedback fast.
HardTechnical
0 practiced
Implement (or describe implementation) of a safe binary protocol parser in Rust that accepts optional fields and unknown extensions. Requirements: never panic on truncated or malformed input, reject malformed lengths, allow forward-compatible skipping of unknown fields, and include fuzz tests. Explain how Rust's ownership and type system help safety.
EasyTechnical
0 practiced
Write a Python function 'safe_divide(a, b)' that returns the floating-point result of a/b. Requirements: if b is zero, log a warning and return None; if inputs are not numeric, raise TypeError; handle infinities and NaN by raising ValueError. Provide unit tests that cover edge cases such as a=0, b=0, a=float('inf'), and b=-1.

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