Design a Word Filter (Prefix/Suffix Search)
Design a data structure that supports searching for a word with a given `prefix` and `suffix` simultaneously. Consider using two Tries or a single specialized Trie.
Why Interviewers Ask This
Uber asks this to evaluate a candidate's ability to optimize for both time and space complexity in real-world search scenarios. They specifically test if you can design a data structure that handles bidirectional constraints efficiently, moving beyond basic linear scans to advanced tree manipulations or suffix-prefix combinations.
How to Answer This Question
1. Clarify requirements immediately: Ask about case sensitivity, duplicate words, and expected query volume versus insertion frequency to determine if optimization is needed. 2. Propose the brute-force approach first to establish a baseline, explaining its O(N) lookup cost per word to show your analytical foundation. 3. Introduce the optimized solution using two separate Tries (one for prefixes, one for suffixes) or a single Trie with combined keys, discussing the trade-offs in memory usage. 4. Walk through the algorithm step-by-step, detailing how you traverse the prefix trie and suffix trie simultaneously to find the intersection of valid indices. 5. Analyze the final Big-O notation for both build and search operations, explicitly mentioning how this scales for Uber's high-volume geospatial or routing data.
Key Points to Cover
- Demonstrating the ability to balance Time vs Space complexity trade-offs effectively
- Proposing a solution that achieves O(L) query time rather than O(N)
- Clearly articulating the difference between a brute-force approach and an optimized Trie structure
- Handling edge cases like overlapping indices and duplicate words in the dataset
- Connecting the technical solution to real-world scalability needs typical of Uber's platform
Sample Answer
To solve the Word Filter problem efficiently, I would first clarify if we need exact matches or partial overlaps, assuming standard exact matching for now. A naive approach checking every word against both prefix and suf…
Common Mistakes to Avoid
- Focusing only on the prefix search and ignoring the simultaneous suffix constraint requirement
- Implementing a brute-force solution without attempting to optimize for large-scale data
- Failing to explain the space complexity implications of duplicating data across multiple structures
- Not clarifying whether the input list contains duplicates before designing the index storage mechanism
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