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Google·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Google SWE coding round, basically a Number of Islands variant. Pretty standard graph traversal problem but I still managed to second-guess myself halfway through.

Questions Asked (1)

Q1

Given a 2D grid of '1's (land) and '0's (water), count the number of islands where an island is a group of horizontally or vertically connected land cells. Implement a solution in Python using DFS or BFS.

Algorithms & Data Structures
Author's notes

Went with DFS.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints and edge cases, then propose a DFS or BFS solution that iterates through each cell, and when a '1' is found, increments the island count and sinks the entire island by marking connected land cells as '0'. Analyze time and space complexity, and discuss potential optimizations or trade-offs.

Pro tip: Mention that you can avoid modifying the input by using a separate visited set, but if modification is allowed, in-place marking is more space-efficient. Also, discuss how to handle very large grids that don't fit in memory, showing awareness of scalability.

1. Clarify requirements and constraints

Ask about grid size, whether the input can be modified, and if diagonal connections count. Confirm that the grid is rectangular and contains only '0's and '1's.

2. Choose traversal method

Decide between DFS (recursive or iterative) and BFS. Mention that DFS is simpler but may cause stack overflow for large grids; BFS uses a queue and is safer for deep recursion.

3. Outline algorithm

Iterate through each cell. When a '1' is found, increment island count and perform DFS/BFS to mark all connected land cells as visited (e.g., set to '0'). Continue until all cells are processed.

4. Analyze complexity

Time complexity is O(M×N) since each cell is visited once. Space complexity is O(M×N) in the worst case for the recursion stack or queue, but can be O(min(M,N)) with optimized BFS.

5. Discuss edge cases and optimizations

Handle empty grid, all water, all land, and single row/column. Mention iterative DFS to avoid recursion limits, and union-find as an alternative approach.

Key Points to Mention

  • Time and space complexity analysis
  • DFS vs BFS trade-offs (recursion depth, queue memory)
  • In-place modification vs using a visited set
  • Handling edge cases (empty grid, no islands, all land)
  • Iterative DFS to prevent stack overflow
  • Alternative approaches like Union-Find

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