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flipster·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Had a technical screen at Flipster that was pretty much one coding question the whole time. Classic stock problem, nothing too exotic, but the O(1) space constraint is where they're actually testing you.

Questions Asked (1)

Q1

Given an array of daily stock prices, find the maximum profit from a single buy-then-sell transaction. Return 0 if no profit is possible. Must run in O(n) time and O(1) space.

Algorithms & Data Structures
Author's notes

The question itself is pretty standard but I fumbled around with a brute force explanation first before they nudged me toward the linear approach.

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AI HintsAI Generated

Suggested Approach

Use a single pass through the array, tracking the minimum price seen so far and the maximum profit achievable at each step. This greedy approach ensures O(n) time and O(1) space by updating the minimum and profit in constant time per element.

Pro tip: Explicitly state the time and space complexity and why the greedy approach is optimal, as interviewers often look for candidates who can justify their solution's efficiency. Also, mention edge cases like empty array or decreasing prices to show thoroughness.

1. Clarify the problem

Confirm that you need to find the maximum profit from one buy and one sell, with buy before sell, and return 0 if no profit. Ask about input constraints (e.g., array size, price range) to ensure your solution handles all cases.

2. Outline the greedy approach

Explain that you will iterate through the array once, keeping track of the minimum price seen so far and the maximum profit. At each price, update the minimum and then compute the potential profit if sold at the current price, updating the maximum profit if larger.

3. Walk through an example

Use a small example like [7,1,5,3,6,4] to demonstrate how the algorithm works step by step, showing the updates to min_price and max_profit. This helps the interviewer follow your logic.

4. Analyze complexity

State that the algorithm runs in O(n) time because it makes a single pass, and O(1) space because it only uses a few variables. Emphasize that this meets the problem's requirements.

5. Handle edge cases

Mention that if the array is empty or has only one element, the profit is 0. Also, if prices are strictly decreasing, the algorithm correctly returns 0.

Key Points to Mention

  • Single pass through the array
  • Tracking minimum price and maximum profit
  • Greedy algorithm
  • Time complexity O(n) and space complexity O(1)
  • Edge cases: empty array, single element, decreasing prices
  • Buy must occur before sell

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