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Amazon·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Amazon coding round for a software engineer role. One algorithmic problem, greedy/DP flavor, not too bad once you see the pattern but I fumbled around for a bit before it clicked.

Questions Asked (1)

Q1

You have n cities in a line, each with a population value. A binary string tells you which cities have a security unit. Each unit can optionally move one city to the left (except the unit at city 1). A city is protected if at least one unit ends up there. Maximize the total population of protected cities.

Algorithms & Data Structures
Author's notes

Took me longer than I'd like to admit to stop thinking about this as a graph problem.

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AI HintsAI Generated

Suggested Approach

Model the problem as a dynamic programming problem where you process cities from left to right, keeping track of whether the previous unit moved to the current city. Define states based on the position and the action of the unit at the previous city, then maximize the sum of populations of protected cities.

Pro tip: Clarify that units can only move left, so a unit at city i can protect i or i-1, but not i+1. This asymmetry simplifies the DP because decisions only affect the current and next city.

1. Understand the problem and constraints

Restate the problem: n cities in a line, each with a population, and a binary string indicating initial unit positions. Each unit can stay or move one city left (except city 1). A city is protected if at least one unit ends there. Goal: maximize total protected population.

2. Define DP state

Let dp[i][moved] represent the maximum protected population considering cities 1..i, where 'moved' indicates whether the unit at city i (if any) has moved to city i-1. Alternatively, use dp[i][prev_action] where prev_action indicates if the unit from city i-1 moved to city i.

3. Establish transitions

For each city i, consider possibilities based on whether there is a unit at i and whether it moves. Ensure city i is protected if either a unit stays at i or a unit from i+1 moves to i. Update DP accordingly, taking max of valid configurations.

4. Handle base cases and boundaries

Initialize DP for city 1: if there's a unit at city 1, it cannot move left, so it must stay (protecting city 1). If no unit, city 1 is unprotected unless a unit from city 2 moves to it (handled later).

5. Compute final answer and optimize

Iterate through cities, filling DP table. The answer is the maximum value at city n considering all valid states. Discuss time and space complexity: O(n) time and O(1) space if optimized.

Key Points to Mention

  • Dynamic programming with states representing the action of the unit at the current city.
  • The leftward-only movement means decisions are local and only affect adjacent cities.
  • Base case handling for city 1 where no left move is possible.
  • Transition considering whether a city is protected by its own unit or a unit from the right.
  • Time complexity O(n) and space complexity O(1) after optimization.
  • Edge cases: no units, all units, units at boundaries.

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