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Apple·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Apple SWE interview with a grid-based island problem. Pretty standard algorithmic stuff but the follow-up caught me a bit flat-footed.

Questions Asked (2)

Q1

Given a binary matrix of 0s and 1s, implement a function sizeOfIsland(grid, r, c) that returns the number of cells in the island containing cell (r, c), or 0 if the cell is water or out of bounds. You can mutate the grid or use a separate visited structure. Walk through your algorithm, state your base cases, and analyze time and space complexity.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

I went with DFS and chose to mutate the grid by flipping visited 1s to 0s.

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AI HintsAI Generated

Suggested Approach

Clarify the problem constraints and edge cases, then propose a depth-first search (DFS) or breadth-first search (BFS) traversal from the given cell to count connected land cells. Discuss mutating the grid versus using a visited set, and analyze time and space complexity.

Pro tip: Mention that mutating the grid to mark visited cells is often preferred in interviews for its O(1) space overhead, but always ask if mutation is allowed. Also, explicitly handle out-of-bounds and water cells as base cases to avoid errors.

1. Clarify and Validate

Restate the problem, confirm input types, and discuss edge cases such as out-of-bounds indices, water cells, and empty grid. Ask if grid mutation is permitted.

2. Choose Traversal Strategy

Decide between DFS (recursive or iterative) and BFS. Explain your choice based on constraints like grid size and recursion depth limits.

3. Define Base Cases and Recursive Step

For DFS: base cases are out-of-bounds, water, or already visited. Otherwise, mark visited and recursively explore all four directions, summing counts.

4. Implement and Walk Through Example

Write pseudocode or code, then trace through a small example to verify correctness, including edge cases.

5. Analyze Complexity and Trade-offs

State time complexity O(N) where N is number of cells in the island, and space complexity O(N) for recursion stack or visited set. Discuss trade-offs between mutation and extra space.

Key Points to Mention

  • Base cases: out-of-bounds, water (0), or already visited.
  • Marking visited cells: mutate grid (e.g., set to 0 or -1) or use a separate visited matrix/set.
  • Traversal order: explore all four directions (up, down, left, right).
  • Time complexity: O(N) where N is the number of cells in the island (or grid in worst case).
  • Space complexity: O(N) for recursion stack (DFS) or queue (BFS), or O(N) for visited set if not mutating.
  • Trade-offs: mutation saves space but may not be allowed; visited set preserves input but uses extra space.

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

Q2

Adapt your solution to find the size of the largest island across the entire grid.

Algorithms & Data Structures
Author's notes

Basically just wrap the original function in a loop over every cell and track the max.

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AI HintsAI Generated

Suggested Approach

Clarify that the problem is to find the maximum island size in a binary grid, likely after changing at most one 0 to 1. Use DFS/BFS with union-find to compute island sizes, then evaluate each 0 by summing the sizes of adjacent distinct islands plus one. Handle edge cases like no zeros or all ones.

Pro tip: Mention that you would first solve the simpler 'max island size without flipping' to establish a baseline, then extend it, showing incremental problem-solving and awareness of Apple's emphasis on clean, efficient code.

1. Clarify the problem

Confirm whether the task is to find the largest island after changing at most one 0 to 1, and discuss constraints like grid size and whether diagonal connections count.

2. Choose an approach

Decide between DFS/BFS with a visited set or union-find. Union-find is often cleaner for this problem because it efficiently tracks island sizes and merges components.

3. Compute island sizes

Traverse the grid to identify all islands, assign each a unique ID, and record their sizes using union-find or DFS/BFS.

4. Evaluate each zero

For each 0, collect the unique IDs of adjacent islands, sum their sizes, add 1 for the flipped cell, and update the maximum.

5. Handle edge cases and return

If there are no zeros, return the size of the largest existing island. Otherwise, return the maximum found in step 4.

Key Points to Mention

  • Time and space complexity: O(N*M) time and O(N*M) space for union-find or DFS.
  • Use of union-find with path compression and union by rank for efficiency.
  • Handling of edge cases: all 1s, all 0s, single row/column.
  • Avoiding double-counting adjacent islands by using a set of unique island IDs.
  • Potential optimization: only consider zeros that are adjacent to at least one island.
  • Clarify that diagonal connections are not considered unless specified.

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