Software Engineer · Phone Screen · Live Coding

Stripe — Software Engineer

Level: Intern

Round: Phone Screen · Type: Live Coding · Difficulty: 6/10 · Duration: 60 min · Interviewer: Neutral

Topics: Graph Theory, Dynamic Programming, Greedy Algorithms, Backtracking

Location: San Francisco Bay Area

Interview date: 2026-02-15

Summary

This phone screen consisted of two coding questions related to debt minimization and finding the cheapest flights with a limited number of transfers.

Details

I had a phone screen where I was asked two coding questions:

Question 1: Minimize Multi-Person Debt Settlement The problem was to find the minimum number of transactions to settle debts among a group of people, given multiple loan records, ensuring everyone's balance returns to zero.

My Approach: First, I calculated each person's net balance and focused only on those with non-zero balances. Then, I used backtracking or a greedy approach to match positive and negative amounts as much as possible. For example, someone owing 50 can directly pay someone who is owed 50, resolving two people's issues with one transaction and minimizing the total number of transactions.

Follow-up: If the debt relationships are very complex, involving hundreds of people, can your algorithm maintain efficiency?

Question 2: Cheapest Flights with Limited Transfers Given a list of flights and their respective prices, find the lowest cost path from a starting point to a destination within k transfers.

My Approach: This is a typical graph theory shortest path problem. I used dynamic programming, where dp[i][k] represents the minimum fare to reach point i within k steps. Alternatively, I considered using an improved Dijkstra's algorithm, adding the current number of steps to the priority queue to ensure it doesn't exceed k transfers while seeking the lowest price.

Follow-up: If the route network is large or needs to support real-time price updates, how would you optimize it?