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Pinterest·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
May 2026Remote

Summary

Pinterest phone screen for a software engineer role. One coding question, pretty focused on sorting and search with some follow-up discussion about edge cases. Nothing too wild but the date comparison piece tripped me up a bit.

Questions Asked (1)

Q1

You're given a list of log entries, each with a date string attached. Sort them by date, then use binary search to find the index of a log entry matching a given target date. How do you compare date strings correctly, and how do you handle duplicates or a date that doesn't exist in the list?

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

The sorting part I got fine, but I stumbled on the date comparison piece.

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AI HintsAI Generated

Suggested Approach

First, clarify the date string format and whether lexicographic sorting is valid (e.g., ISO 8601). Then, outline a sorting step (e.g., using a stable sort) and a binary search that handles duplicates by finding the first or last occurrence, and returns a sentinel (like -1) if the target is absent. Discuss trade-offs such as time complexity and the importance of consistent date formatting.

Pro tip: Mention that if the date strings are not in a sortable format (e.g., 'MM/DD/YYYY'), you must parse them into a comparable form (like Unix timestamps) before sorting; otherwise, lexicographic order will be incorrect. Also, note that binary search on duplicates can be adapted to return any matching index or a range, depending on requirements.

1. Clarify date format and comparability

Ask or state the format of the date strings (e.g., ISO 8601, RFC 3339) and confirm if lexicographic comparison yields chronological order. If not, plan to parse dates into a comparable type.

2. Sort the log entries

Sort the list by date using an appropriate comparison function. If dates are parsed, sort by the parsed value; otherwise, use string comparison. Ensure the sort is stable if preserving original order for duplicates matters.

3. Implement binary search with duplicate handling

Perform binary search on the sorted list. For duplicates, decide whether to return the first, last, or any matching index. Use a modified binary search that continues searching left or right after finding a match.

4. Handle target not found

If the target date is not present, return a sentinel value (e.g., -1) or the insertion point. Clearly state the return value and its meaning.

5. Analyze complexity and trade-offs

State that sorting takes O(n log n) and binary search takes O(log n). Discuss space complexity and whether in-place sorting is possible. Mention that if multiple queries are expected, sorting once and reusing is efficient.

Key Points to Mention

  • Date string format and whether lexicographic order equals chronological order (e.g., ISO 8601 is sortable).
  • Parsing non-sortable date strings into a comparable format (e.g., Unix timestamp) before sorting.
  • Stable sorting to preserve original order of duplicate dates if needed.
  • Binary search variants for finding first/last occurrence of duplicates (lower_bound/upper_bound).
  • Return value for missing target (e.g., -1 or insertion index) and its implications.
  • Time and space complexity: O(n log n) for sorting, O(log n) for search, and O(1) extra space if in-place.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.