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Weride·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026Remote

Summary

Five phone screen rounds for a software engineer role at Weride, each split between resume walkthrough and a coding problem. Interviews were scheduled around China time, so evening slots were on the table. The coding portion focused on Tries.

Questions Asked (1)

Q1

Implement or work through a problem involving a Trie data structure.

Algorithms & Data Structures
Author's notes

Five rounds and they kept the coding portion pretty focused.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem requirements and constraints, then explain the Trie structure and its advantages for prefix-based operations. Walk through the implementation step-by-step, discussing time and space complexity, and consider edge cases and potential optimizations.

Pro tip: Mention real-world applications of Tries, such as autocomplete or IP routing, to show practical understanding. Also, discuss memory optimization techniques like using a hash map for children or compressed Tries (radix trees) when appropriate.

1. Clarify Requirements

Ask questions to understand the problem scope, input constraints, and expected operations (insert, search, startsWith, etc.). Confirm if the Trie should support deletion or other advanced features.

2. Design the Trie

Explain the Trie node structure, typically with an array or hash map for children and a boolean flag for end-of-word. Discuss trade-offs between fixed-size arrays and dynamic structures.

3. Implement Operations

Code the insert, search, and prefix search methods, ensuring correct traversal and flag updates. Handle edge cases like empty strings and null inputs.

4. Analyze Complexity

State the time complexity for each operation (O(m) where m is key length) and space complexity (O(total characters * alphabet size) or O(total characters) with hash maps).

5. Test and Optimize

Walk through test cases, including normal and edge cases. Suggest optimizations like using a compressed Trie or limiting alphabet size if applicable.

Key Points to Mention

  • Trie node structure with children and end-of-word flag
  • Time complexity: O(m) for insert/search/prefix search, where m is key length
  • Space complexity: O(N * A) for array-based or O(N) for hash map-based, where N is total characters and A is alphabet size
  • Use cases: autocomplete, spell check, IP routing, T9 predictive text
  • Edge cases: empty string, duplicate insertions, deletion (if required)
  • Optimizations: compressed Trie (radix tree), ternary search tree, using hash maps for sparse children

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