← Perplexity Interview Insights
Clarify the input format and citation pattern, then propose an efficient solution using regex or a parser to extract citation numbers. Discuss trade-offs between simplicity and robustness, and consider edge cases like multiple citations per paragraph and duplicate numbers.
Pro tip: Mention that you would validate the extracted numbers against the source list to handle out-of-range citations, and discuss how to scale the solution for large documents.
Ask about the exact format of citations (e.g., [1], (1), superscript) and whether citations can be ranges or comma-separated. Confirm if duplicates should be removed and if the output should be sorted.
Decide between regex-based extraction for simplicity or a more robust parser if citations are complex. Consider performance implications for large inputs.
Account for multiple citations in one paragraph, citations with spaces, and invalid numbers. Discuss how to handle duplicates and whether to preserve order.
Write code to extract numbers, possibly using a set to deduplicate. Test with sample paragraphs including edge cases.
Compare regex vs. parser in terms of maintainability and performance. Mention potential optimizations like streaming for large documents.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.