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Netflix·Software Engineer·Onsite - Coding / Algorithms·Intermediate

IntermediatePrefer not to say
May 2026

Summary

Netflix SWE coding round with two problems. Nothing too wild but the second one had more design discussion than I expected for a coding interview.

Questions Asked (2)

Q1

Given a set of tasks and their dependencies, return a valid execution order where every task runs after its prerequisites. If a cycle exists and no valid order is possible, return an indication that the schedule is impossible.

Algorithms & Data Structures
Author's notes

Topological sort, basically.

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AI HintsAI Generated

Suggested Approach

Model the tasks and dependencies as a directed graph and perform a topological sort using Kahn's algorithm (BFS with in-degree tracking) or DFS with cycle detection. If the topological order contains all tasks, return it; otherwise, report that no valid schedule exists due to a cycle.

Pro tip: Explicitly discuss how you would handle large-scale dependency graphs, such as using iterative DFS to avoid stack overflow or parallelizing the topological sort for distributed systems, showing awareness of Netflix's scale.

1. Clarify the problem and assumptions

Confirm the input format (e.g., adjacency list or edge list), whether tasks are uniquely identified, and if multiple valid orders are acceptable. Ask about constraints like graph size or performance requirements.

2. Choose an algorithm

Select topological sort via Kahn's algorithm (BFS) or DFS with cycle detection. Explain why it fits: O(V+E) time, handles cycles, and produces a valid order.

3. Walk through the algorithm

Describe the steps: compute in-degrees, initialize a queue with zero in-degree nodes, process nodes while decrementing in-degrees of neighbors, and enqueue when in-degree becomes zero. For DFS, use recursion with temporary marks to detect cycles.

4. Handle cycles and edge cases

If the result list size is less than the number of tasks, a cycle exists; return an error or empty list. Discuss edge cases: empty graph, disconnected components, self-loops, and duplicate edges.

5. Analyze complexity and test

State time and space complexity: O(V+E) time, O(V) space. Suggest testing with acyclic graphs, cyclic graphs, and large graphs to ensure correctness and performance.

Key Points to Mention

  • Topological sorting is the standard approach for dependency resolution.
  • Kahn's algorithm (BFS) vs. DFS with cycle detection: trade-offs and implementation details.
  • Cycle detection: if the topological order doesn't include all nodes, a cycle exists.
  • Time and space complexity: O(V+E) time, O(V) space.
  • Handling large graphs: iterative DFS to avoid stack overflow, or parallel processing.
  • Real-world applications: build systems, task scheduling, package managers.

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

Q2

Design and implement a command executor that supports execute and undo operations. The execute method should run a command and record enough state to reverse it, and undo should revert the most recent un-undone command. How would you handle edge cases like calling undo when nothing has been executed?

System DesignTechnical Trade-offs
Author's notes

This one took more time than I budgeted.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and defining the Command interface with execute and undo methods. Then design a CommandInvoker that maintains a stack of executed commands, handling edge cases like empty stack by throwing a custom exception or no-op. Discuss trade-offs such as memory usage, thread safety, and whether to support redo.

Pro tip: Mention that you would use a stack to track commands and consider using the Memento pattern to capture state for undo, but be mindful of memory overhead for large states. Also, proactively discuss how to handle exceptions during execute to avoid corrupting the undo stack.

1. Clarify Requirements and Scope

Ask about expected command types, whether redo is needed, thread safety, and persistence requirements. This shows you think about the broader context before diving into code.

2. Define Command Interface and Concrete Commands

Design an interface with execute() and undo() methods. Each concrete command encapsulates the action and the state needed to reverse it, following the Command pattern.

3. Implement Command Invoker with Undo Stack

Create an invoker that holds a stack of executed commands. On execute, run the command and push it onto the stack. On undo, pop the most recent command and call its undo method.

4. Handle Edge Cases and Errors

For undo when stack is empty, throw a custom exception like NoCommandToUndoException or return a boolean indicating failure. Also consider what happens if execute fails midway—ensure the command is not pushed or is rolled back.

5. Discuss Trade-offs and Extensions

Talk about memory vs. performance (storing full state vs. deltas), thread safety (synchronized stack or concurrent data structure), and optional redo support using a second stack.

Key Points to Mention

  • Command pattern with execute and undo methods
  • Using a stack (LIFO) to track executed commands for undo
  • Edge case: undo on empty stack—throw exception or no-op with logging
  • Exception handling during execute to maintain stack consistency
  • Memory considerations: storing full state vs. deltas, and potential for memory leaks
  • Thread safety: synchronization or concurrent collections if used in multithreaded environment
  • Optional redo functionality using a redo stack

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