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Amazon·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Amazon SWE interview with a graph traversal problem dressed up as a systems/infrastructure scenario. Pretty clever framing but once you see it for what it is, it's just BFS or DFS on a dependency graph.

Questions Asked (1)

Q1

Given a map of services to the services that depend on them, and a set of services being taken offline, return all services that will be affected either directly or transitively (including the stopped ones themselves).

Algorithms & Data StructuresSystem Design
Author's notes

The setup is a bit verbose but it's basically graph reachability.

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AI HintsAI Generated

Suggested Approach

Model the services and dependencies as a directed graph where an edge from A to B means A depends on B. Then perform a traversal (BFS/DFS) starting from all offline services, following reverse dependency edges to find all affected services. Include the initially stopped services in the result set.

Pro tip: Clarify the direction of dependencies upfront: if the map is service -> dependents, you can traverse forward; if it's service -> dependencies, you need to reverse the edges. Also, mention that you'll deduplicate results using a set to avoid duplicates in cyclic graphs.

1. Clarify input/output and edge cases

Confirm the map's direction (service to dependents or dependencies), whether the stopped services are included in the output, and handle edge cases like cycles, multiple stopped services, and services with no dependents.

2. Model as a graph

Represent services as nodes and dependencies as directed edges. If the map is service -> dependencies, reverse the edges to get service -> dependents for forward traversal.

3. Traverse from stopped services

Use BFS or DFS starting from all stopped services, following edges to dependents. Use a visited set to avoid revisiting nodes and handle cycles.

4. Collect and return affected services

The visited set contains all affected services, including the initially stopped ones. Return this set as the result.

5. Analyze complexity and discuss optimizations

State time complexity O(V+E) and space O(V+E). Mention potential optimizations like early termination if only a subset is needed, or parallel traversal for large graphs.

Key Points to Mention

  • Graph representation: adjacency list is efficient for sparse graphs.
  • Traversal algorithm: BFS or DFS, both O(V+E) time.
  • Handling cycles: visited set prevents infinite loops.
  • Multiple starting points: initialize queue/stack with all stopped services.
  • Including stopped services: ensure they are added to the result set.
  • Edge direction: clarify whether map is service->dependents or service->dependencies; reverse if needed.

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