This one took me a while to even get my footing.
Start by understanding the parser's architecture and the JSON spec, then systematically test each component with edge cases to uncover bugs. Prioritize fixes based on severity and impact, and verify each fix with targeted tests to ensure correctness.
Pro tip: Demonstrate a methodical debugging process by writing tests first to reproduce bugs, and communicate your reasoning clearly as you go. This shows engineering maturity and makes your problem-solving transparent.
Review the parser's structure and compare it against the JSON specification to identify potential areas of deviation. Clarify any ambiguities about expected behavior with the interviewer.
Create a comprehensive set of test cases covering all JSON features and edge cases (e.g., nested structures, escape sequences, number formats). Run them to identify failing cases and pinpoint bugs.
Categorize bugs by severity (e.g., crashes vs. incorrect parsing) and fix them one by one, starting with critical issues. Explain your reasoning for each fix and consider potential side effects.
Re-run tests to ensure all bugs are fixed and no regressions are introduced. Refactor code if necessary to improve clarity or performance, but avoid over-engineering.
Summarize the bugs found, the fixes applied, and any trade-offs made (e.g., performance vs. readability). Suggest further improvements or edge cases to handle.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.