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Bloomberg·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

Bloomberg SWE interview with a grid-based word search problem. Pretty standard backtracking territory but still worth thinking through carefully before you open your mouth.

Questions Asked (1)

Q1

Given an m x n grid of characters and a target word, determine whether the word can be formed by following a path of horizontally or vertically adjacent cells, where no cell is visited more than once.

Algorithms & Data Structures
Author's notes

Went with DFS plus backtracking which is the right call.

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AI HintsAI Generated

Suggested Approach

Use depth-first search (DFS) with backtracking to explore all possible paths from each cell that matches the first character of the word. At each step, check if the current cell matches the next character, mark it as visited, and recursively explore its four neighbors. If any path forms the word, return true; otherwise, backtrack and continue.

Pro tip: Mention that you can optimize space by temporarily modifying the grid to mark visited cells (e.g., replacing with a special character) instead of using a separate visited matrix, and restore it during backtracking. This shows attention to memory efficiency and in-place modification skills.

1. Clarify and Validate

Confirm the problem constraints: grid dimensions, character set, whether the word can be empty, and if diagonal moves are allowed. Also discuss edge cases like empty grid or word longer than total cells.

2. Choose Algorithm

Select DFS with backtracking as the primary approach. Explain why BFS is less suitable due to the need to track visited cells per path, which is naturally handled by DFS recursion.

3. Design DFS Function

Define a recursive function that takes the current cell coordinates and the index in the word. Base case: if index equals word length, return true. Check bounds, character match, and visited status before recursing.

4. Handle Visited Cells

Mark the current cell as visited before exploring neighbors. After exploring, unmark it (backtrack) to allow other paths to use it. Discuss using a separate boolean matrix or in-place modification.

5. Iterate and Optimize

Iterate over all cells as starting points. If any DFS returns true, return true. Discuss pruning: if the remaining word length exceeds available unvisited cells, return false early.

Key Points to Mention

  • Depth-first search (DFS) with backtracking is the standard approach for this path-finding problem.
  • Time complexity is O(m * n * 4^L) in the worst case, where L is the word length, due to exploring up to 4 directions at each step.
  • Space complexity is O(L) for the recursion stack, plus O(m*n) if using a separate visited matrix.
  • Backtracking is essential to unmark cells after exploring a path, ensuring other paths can reuse them.
  • Pruning techniques: check if the word length exceeds total cells, or if the count of each character in the grid is insufficient.
  • Edge cases: empty word (return true), word longer than grid cells, and single-cell grid.

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