How do you implement a Trie data structure for prefix searching?
This problem requires building a Trie to store strings and efficiently query prefixes. It tests tree construction and string manipulation skills.
Why Interviewers Ask This
Interviewers ask this to evaluate data structure design skills and string handling capabilities. They want to see if you understand how Tries optimize prefix searches compared to hashing or linear scans. It demonstrates structural design and node management.
How to Answer This Question
Describe the Trie node structure containing a map of children and a boolean flag for end-of-word. Explain the insertion process: traverse or create nodes for each character. Mark the end node. For search, traverse the path; if it exists and is marked end, return true. For prefix, just check existence of the path. Discuss time complexity relative to string length.
Key Points to Cover
- Node structure definition
- Character-by-character traversal
- End-of-word marking
- Prefix vs exact search
Sample Answer
A Trie is implemented using a node class where each node has a dictionary of children and a flag indicating if a word ends there. To insert a word, I traverse the tree character by character, creating new nodes as needed…
Common Mistakes to Avoid
- Forgetting to mark end-of-word nodes
- Using fixed-size arrays instead of maps for sparse alphabets
- Incorrectly handling case sensitivity
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