Recall & Review
beginner
What is a Trie data structure?
A Trie is a tree-like data structure that stores a dynamic set of strings, where each node represents a character. It is used to efficiently search for words with common prefixes.
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beginner
How does a Trie help in implementing an autocomplete system?
A Trie allows quick lookup of all words that start with a given prefix by traversing nodes corresponding to the prefix characters, then collecting all descendant words.
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intermediate
What is the time complexity to insert a word of length n into a Trie?
The time complexity is O(n), where n is the length of the word, because each character is inserted one by one along the path in the Trie.
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intermediate
Explain how to search for all words with a given prefix in a Trie.
First, traverse the Trie nodes matching the prefix characters. Then, perform a depth-first search from that node to collect all complete words that start with the prefix.
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intermediate
What is the main advantage of using a Trie over a hash map for autocomplete?
Trie stores words in a prefix-sharing way, which saves space and allows efficient prefix searches, while hash maps do not support prefix queries efficiently.
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What does each node in a Trie represent?
✗ Incorrect
Each node in a Trie represents a single character of a word.
What is the first step to find autocomplete suggestions for a prefix in a Trie?
✗ Incorrect
You first traverse the Trie nodes that match the prefix characters.
What is the time complexity to search for a prefix of length n in a Trie?
✗ Incorrect
Searching for a prefix takes O(n) time, where n is the prefix length.
Which of these is NOT a benefit of using a Trie for autocomplete?
✗ Incorrect
Tries do not automatically sort words by frequency.
What data structure is commonly used to store children nodes in a Trie?
✗ Incorrect
Children nodes are stored in arrays or maps keyed by characters.
Describe how to build an autocomplete system using a Trie.
Think about storing words and searching prefixes.
You got /3 concepts.
Explain why Tries are preferred over hash maps for prefix-based searches.
Consider how data is organized and searched.
You got /3 concepts.