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eBay·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Interviewed for a software engineer role at eBay and got a classic graph traversal problem. Nothing too surprising but it's the kind of question where you either know the pattern or you're fumbling around for ten minutes.

Questions Asked (1)

Q1

Given a 2D grid of '1's (land) and '0's (water), count the number of distinct connected land regions, where connections are only horizontal or vertical.

Algorithms & Data Structures
Author's notes

Classic islands problem.

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AI HintsAI Generated

Suggested Approach

Treat the grid as a graph and use DFS/BFS to explore each connected component of land. Iterate through each cell; when you find an unvisited '1', increment the count and traverse all connected land cells, marking them as visited to avoid recounting.

Pro tip: Mention that you can optimize space by modifying the grid in-place (e.g., setting visited land to '0') if allowed, and discuss trade-offs between DFS (recursion depth risk) and BFS (queue memory).

1. Clarify and Confirm

Restate the problem to ensure understanding: count connected components of '1's using 4-directional adjacency. Ask about grid size limits, mutability, and edge cases (empty grid, all water, all land).

2. Choose Traversal Method

Decide between DFS (recursive or iterative) and BFS. Consider constraints: DFS recursion may cause stack overflow for large grids; BFS uses a queue but avoids recursion limits.

3. Implement Traversal

Iterate through each cell. When encountering an unvisited '1', increment the island count and perform DFS/BFS to mark all connected land cells as visited (e.g., set to '0' or use a visited matrix).

4. Handle Boundaries and Directions

During traversal, check for out-of-bounds indices and only move in four directions (up, down, left, right). Ensure water cells are skipped.

5. Analyze Complexity and Test

State time complexity O(M×N) and space complexity O(M×N) in worst case (e.g., all land). Walk through edge cases and test with a small example.

Key Points to Mention

  • Graph traversal: DFS or BFS to explore connected components.
  • Visited tracking: modify grid in-place or use a separate visited matrix.
  • Time complexity: O(M×N) where M and N are grid dimensions.
  • Space complexity: O(M×N) worst-case for recursion stack or queue.
  • Edge cases: empty grid, no land, all land, single row/column.
  • Trade-offs: DFS recursion depth vs. BFS queue memory; in-place modification vs. extra space.

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