Word Search II
Given a 2D board and a list of words, find all words on the board. The search must be optimized using a Trie and Backtracking.
Why Interviewers Ask This
Stripe values engineers who can balance algorithmic rigor with practical system performance. This question tests your ability to optimize brute-force search using a Trie for prefix pruning, demonstrating deep understanding of space-time trade-offs. It evaluates whether you can handle complex backtracking without hitting Time Limit Exceeded errors, a critical skill for high-throughput payment systems.
How to Answer This Question
1. Clarify constraints: Ask about board dimensions and word list size to determine if a simple DFS is viable or if optimization is mandatory.
2. Propose the Trie structure: Explain that inserting all words into a Trie allows early termination during traversal when a path no longer matches any word prefix.
3. Define the backtracking logic: Describe iterating through every cell, initiating a DFS, marking visited cells to prevent cycles, and backtracking by unmarking them.
4. Discuss optimization details: Mention removing found words from the Trie to avoid re-scanning and handling duplicate word detection efficiently.
5. Analyze complexity: Calculate time complexity as O(M*N*4^L) where L is max word length, noting how the Trie reduces the effective branching factor significantly compared to checking each word individually.
Key Points to Cover
- Explicitly mentioning the Trie data structure for prefix-based pruning
- Demonstrating clear backtracking mechanics including state restoration
- Discussing the removal of found words to optimize subsequent searches
- Providing accurate time and space complexity analysis
- Connecting the algorithm's efficiency to real-world system constraints
Sample Answer
To solve this efficiently, I would first build a Trie from the given list of words. This allows us to check prefixes in constant time relative to the depth of the node. If we start a search from a specific cell on the bo…
Common Mistakes to Avoid
- Failing to use a Trie and instead checking every word against every path, causing TLE
- Forgetting to mark cells as visited during recursion, leading to infinite loops
- Not backtracking (unmarking cells) after returning from a recursive call
- Ignoring duplicate word handling, which can cause incorrect result sets
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