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WhatsApp·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Jun 2026

Summary

WhatsApp coding interview with a classic board game problem. Short on details but the question itself is a decent algorithmic workout if you've never thought about it before.

Questions Asked (1)

Q1

Given a Boggle board, find all valid words that can be formed from adjacent letters.

Algorithms & Data Structures
Author's notes

This is a graph traversal problem at its core but the trick is pruning.

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AI HintsAI Generated

Suggested Approach

Model the Boggle board as a graph and use DFS with backtracking to explore all possible paths from each cell, checking prefixes against a trie or hash set of valid words. Optimize by pruning paths that cannot form any valid word, and consider using a trie for efficient prefix lookup.

Pro tip: Discuss trade-offs between using a trie versus a hash set for the dictionary, and mention how to handle duplicate words and the 'visited' state efficiently. Also, clarify assumptions about board size, word length, and dictionary size to tailor the solution.

1. Clarify requirements and constraints

Ask about board dimensions, dictionary size, whether words can be reused, and if diagonal moves are allowed. Confirm output format (list of words, sorted, etc.).

2. Choose data structures

Decide on a trie for the dictionary to enable prefix pruning, and a 2D boolean array or in-place marking for visited cells. Alternatively, use a hash set if dictionary is small.

3. Design the DFS backtracking algorithm

For each cell, start DFS: if current prefix is a valid word, add to results; if it's a prefix of any word, continue exploring neighbors. Mark cell as visited before recursion and unmark after.

4. Implement optimizations

Prune branches when prefix is not in trie. Use a set to avoid duplicate words. Consider early termination if maximum word length is known.

5. Analyze complexity and test

Discuss time complexity: O(N*M*8^L) worst-case, but trie pruning reduces it. Space: O(L) recursion depth plus trie storage. Walk through a small example.

Key Points to Mention

  • Use DFS with backtracking to explore all paths from each cell.
  • Employ a trie for the dictionary to enable efficient prefix checking and pruning.
  • Track visited cells to avoid reusing the same cell in a single word.
  • Handle duplicate words by storing results in a set or marking trie nodes as found.
  • Consider edge cases: empty board, no valid words, single cell, large dictionary.
  • Discuss time and space complexity, and potential optimizations like early termination.

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