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Uber·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

Uber SWE coding round, just one algorithmic problem the whole session. Pretty focused interview, nothing behavioral at all.

Questions Asked (1)

Q1

Given an array of prices, for each item find the first later item whose price is less than or equal to it and use that as a discount. Return the array of final discounted prices.

Algorithms & Data Structures
Author's notes

Classic monotonic stack problem once you see it, but I spent a few minutes trying to brute force it first.

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AI HintsAI Generated

Suggested Approach

Clarify the problem and edge cases, then propose an efficient solution using a monotonic stack to find the next smaller or equal element for each price in O(n) time. Walk through the algorithm with a small example, then discuss implementation details and complexity.

Pro tip: Mention that this is a classic 'Next Smaller Element' problem and that a monotonic stack is optimal; also note that handling equal prices correctly (using <=) is crucial to avoid off-by-one errors.

1. Clarify the problem

Confirm that for each item, we need the first subsequent item with price <= current price, and if none exists, the discount is 0 (final price unchanged).

2. Choose the right data structure

Recognize that a monotonic stack efficiently finds the next smaller or equal element in O(n) time by maintaining a stack of indices with increasing prices.

3. Outline the algorithm

Iterate through the array; while the stack is not empty and the current price is <= the price at the stack's top index, pop and set the discount for that index to the current price. Push the current index onto the stack.

4. Handle remaining items

After the iteration, any indices left in the stack have no later item with a lower or equal price, so their discount remains 0.

5. Analyze complexity and test

State that the time complexity is O(n) and space complexity is O(n) due to the stack. Walk through a small example to verify correctness, including edge cases like all increasing or all equal prices.

Key Points to Mention

  • Monotonic stack technique for next smaller or equal element
  • Time and space complexity: O(n) time, O(n) space
  • Handling equal prices correctly (using <= comparison)
  • Edge cases: empty array, single element, strictly increasing/decreasing prices
  • Alternative approaches (e.g., brute force O(n^2)) and why they are suboptimal
  • In-place modification of the array to store final discounted prices

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