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numeric·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Coding round at Numeric for a software engineer position. One algorithmic problem, greedy with a heap, the kind of question that looks clean on paper but has a few subtle edge cases that can trip you up mid-interview.

Questions Asked (1)

Q1

A spaceship travels from a start position toward a target along a 1-D axis, with a fixed starting fuel and a list of refueling stations (each with a position and fuel amount). Every unit of distance costs one unit of fuel. What is the minimum number of stops needed to reach the target, or -1 if it's impossible?

Algorithms & Data Structures
Author's notes

My first instinct was DP and I started going down that road before catching myself.

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AI HintsAI Generated

Suggested Approach

Model the problem as a greedy algorithm: treat each station as a potential refueling point and always refuel at the station with the most fuel among those reachable with the current fuel. Use a max-heap to efficiently select the best station, and count stops until the target is reached or no stations are reachable.

Pro tip: Clarify that the greedy choice is optimal because refueling at the station with maximum fuel maximizes future reach without increasing the number of stops. Also, mention that if the target is unreachable even after considering all stations, return -1.

1. Understand the problem and constraints

Restate the problem: given start fuel, target distance, and stations (position, fuel), find the minimum stops to reach the target. Note that fuel is consumed at 1 unit per distance, and you can only refuel at stations you pass.

2. Choose the right data structures

Use a max-heap to store fuel amounts of reachable stations. Sort stations by position to process them in order as you travel.

3. Simulate the journey with greedy refueling

Iterate through stations, adding their fuel to the heap when they become reachable. When fuel runs out before the next station or target, pop the max fuel from the heap, add it to current fuel, and increment the stop count.

4. Handle edge cases and termination

If the heap is empty and the target is not reachable, return -1. If the target is reached, return the stop count. Ensure stations beyond the target are ignored.

5. Analyze complexity and test

Time complexity is O(n log n) due to sorting and heap operations. Space complexity is O(n) for the heap. Walk through a small example to verify correctness.

Key Points to Mention

  • Greedy strategy: always refuel at the station with the most fuel among reachable ones.
  • Use a max-heap (priority queue) to efficiently retrieve the maximum fuel.
  • Sort stations by position to process them in order.
  • Track current fuel and stop count; update fuel when refueling.
  • Return -1 if the target cannot be reached even after using all reachable stations.
  • Time complexity O(n log n) and space complexity O(n).

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