Bytedance·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

May 2026

Summary

Bytedance SWE coding round with a DP problem that looked like a simple greedy at first but definitely wasn't. The question had enough edge cases to make you second-guess yourself the whole way through.

Questions Asked (1)

You start at position 0 and need to deliver cargo to a target position T by walking forward. There are charging stations at sorted positions along the way, and at any station you can launch a drone that carries the cargo exactly 10 units forward (no walking cost for that segment). Compute the minimum total walking distance to deliver the cargo to T.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

My first instinct was pure greedy, just launch the drone at every station you pass and call it done.

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AI HintsAI Generated

Suggested Approach

Model the problem as a shortest path on a line where walking edges connect adjacent positions and drone edges connect each station to position+10 with zero cost. Use dynamic programming or Dijkstra to compute the minimum walking distance to T, considering only relevant positions (stations, station+10, and T).

Pro tip: Clarify that drone launches are only from stations and that the drone moves exactly 10 units forward; if T is not exactly reachable, you may need to walk the remainder. Also, consider if multiple drones can be used sequentially from different stations.

1. Understand the problem and constraints

Restate the problem: start at 0, target T, stations at sorted positions, drone moves exactly 10 forward from a station at zero walking cost. Identify that you can walk any distance forward at cost equal to distance.

2. Define state and transitions

Define state as current position. Transitions: walk to any forward position (cost = distance) or if at a station, launch drone to position+10 (cost = 0). Only positions that matter are 0, T, stations, and station+10.

3. Choose algorithm

Since the graph is a DAG (only forward edges), use DP: dp[i] = min walking distance to reach position i. Process positions in increasing order. Alternatively, use Dijkstra for general graphs.

4. Implement and handle edge cases

Initialize dp[0]=0, others infinity. For each position in sorted order, update dp[pos+10] if pos is a station, and update dp[next] for walking. Handle cases where T is before first station, or no stations, or drone overshoots T.

5. Analyze complexity and trade-offs

Time O(N log N) due to sorting (if not already sorted) and O(N) DP. Space O(N). Discuss if greedy works: not always, because using a drone might skip a station that could be useful later.

Key Points to Mention

Graph modeling: nodes are positions, edges are walking (weighted) and drone (zero weight).
Dynamic programming with states as positions, processing in increasing order.
Only consider relevant positions: 0, T, stations, and station+10.
Drone can only be launched from stations and moves exactly 10 units forward.
Edge cases: T before first station, no stations, drone overshoots T, multiple drones.
Complexity: O(N log N) time, O(N) space, and why greedy fails.

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