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Meta·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Apr 2026

Summary

Meta data engineer interview with a trie implementation question. Pretty standard coding round, nothing too surprising.

Questions Asked (1)

Q1

Implement a Trie data structure with insert, search, and prefix search functionality.

Algorithms & Data Structures
Author's notes

I knew the concept but fumbled the implementation a bit.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the requirements and constraints, then design a Trie node with children (e.g., array or hashmap) and an isEndOfWord flag. Implement insert, search, and startsWith methods, and analyze time and space complexity. Consider edge cases like empty strings and large alphabets.

Pro tip: Mention that using a hashmap for children can save space for sparse tries, but an array of size 26 is faster for dense lowercase English alphabets. Also, discuss how to handle deletion if asked, and note that Trie is ideal for autocomplete and spell-check.

1. Clarify requirements and constraints

Ask about the character set (e.g., lowercase English letters), maximum word length, and whether deletion is needed. Confirm the expected time and space complexity.

2. Design the Trie node

Define a TrieNode class with a children data structure (array or hashmap) and a boolean flag isEndOfWord. Explain your choice based on the character set and memory considerations.

3. Implement insert, search, and startsWith

For insert, traverse or create nodes for each character and mark the last node as end of word. For search, traverse and return true only if the last node is marked as end. For startsWith, traverse and return true if the prefix exists, regardless of end flag.

4. Analyze complexity and edge cases

State that time complexity for all operations is O(L) where L is the word length, and space is O(N*L) for N words. Discuss edge cases: empty string, very long words, and non-alphabetic characters.

5. Test with examples and discuss optimizations

Walk through a small example like inserting 'apple' and searching 'app'. Mention possible optimizations like using a ternary search tree or compressed trie (radix tree) for memory efficiency.

Key Points to Mention

  • Trie node structure: children (array/hashmap) and isEndOfWord flag
  • Time complexity: O(L) for insert, search, and startsWith
  • Space complexity: O(N*L) worst case, but can be optimized with hashmaps for sparse data
  • Difference between search and startsWith: search requires isEndOfWord true, startsWith does not
  • Edge cases: empty string, words with common prefixes, and non-alphabetic characters
  • Use cases: autocomplete, spell check, IP routing (longest prefix match)

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