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Instacart·Software Engineer·Technical Phone Screen·Intermediate

IntermediateRejected
May 2026Remote

Summary

Karat screen for a Software Engineer role at Instacart. The coding portion went sideways pretty fast, ran out of time on the main problem and didn't get to run the code, which sealed the outcome.

Questions Asked (1)

Q1

Given a list of stock record objects (each with a date and a price), find the largest absolute price change between chronologically adjacent days. Return the two dates and the price difference.

Algorithms & Data Structures
Author's notes

The part that tripped me up wasn't the algorithm itself, it was figuring out how to extract fields from the record objects.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the input format and edge cases, then propose sorting the records by date and iterating through adjacent pairs to compute absolute differences. Track the maximum difference and return the corresponding dates and difference, discussing time and space complexity.

Pro tip: Mention that if the list is already sorted by date, you can avoid the O(n log n) sort and achieve O(n) time, showing you optimize based on input assumptions. Also, handle ties by returning the first occurrence or clarifying with the interviewer.

1. Clarify requirements and edge cases

Ask about input size, whether dates are unique, if the list is sorted, and how to handle ties or fewer than two records. Confirm the return format (two dates and the difference).

2. Choose an efficient algorithm

Decide to sort the records by date if not already sorted, then iterate through adjacent pairs to compute absolute differences. Alternatively, if sorted, do a single pass.

3. Implement and track maximum

Initialize variables for max difference and the corresponding dates. Loop through the sorted list, compute the absolute difference between consecutive prices, and update the maximum when a larger difference is found.

4. Analyze complexity and test

State the time complexity (O(n log n) due to sorting, or O(n) if already sorted) and space complexity (O(1) extra if sorting in place, or O(n) if creating a sorted copy). Walk through a small example to verify correctness.

Key Points to Mention

  • Sorting the records by date is necessary if the input is not guaranteed to be sorted.
  • Use absolute difference to capture both increases and decreases.
  • Track the maximum difference and the corresponding pair of dates during a single pass after sorting.
  • Time complexity: O(n log n) for sorting, O(n) for the scan; space complexity: O(1) extra if sorting in place, otherwise O(n).
  • Handle edge cases: empty list, single record, duplicate dates, and ties for maximum difference.
  • If the input is already sorted, the solution can be optimized to O(n) time.

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