Why Trie Exists and What Hash Map Cannot Do for Strings in DSA C++ - Quick Recap

Recall & Review

beginner

What is a Trie and why is it used for strings?

A Trie is a tree-like data structure that stores strings by sharing common prefixes. It is used to efficiently search, insert, and delete strings, especially when many strings share prefixes.

beginner

Why can't a hash map efficiently handle prefix-based string queries?

A hash map treats each string as a whole key and does not store information about prefixes. It cannot efficiently find all strings starting with a given prefix without checking every key.

intermediate

How does a Trie improve prefix search compared to a hash map?

A Trie stores strings character by character in a tree structure, allowing quick traversal to the node representing the prefix. This makes prefix searches fast and efficient without scanning all keys.

intermediate

What is a real-life example where Trie is better than a hash map for strings?

In autocomplete systems, Trie quickly finds all words starting with typed letters, while hash maps would need to check all stored words, making Trie faster and more suitable.

intermediate

What is a limitation of using a hash map for string storage compared to Trie?

Hash maps use more memory when storing many strings with common prefixes because they store each string separately, while Trie shares prefix nodes, saving space.

What data structure is best for fast prefix searches in strings?

A Trie

B Hash Map

C Array

D Stack

Trie stores strings by prefixes, enabling fast prefix searches.

Why can't hash maps efficiently find all strings starting with a prefix?

A They only store numbers

B They use too much memory

C They are slower than arrays

D They store strings as whole keys without prefix info

Hash maps treat keys as whole strings, so prefix info is not stored.

Which of these is a key advantage of Trie over hash map?

A Faster insertion of numbers

B Supports prefix search efficiently

C Uses less memory for unrelated strings

D Better for sorting integers

Trie is designed to efficiently support prefix-based operations.

In which scenario is Trie preferred over hash map?

A Storing unrelated keys

B Counting unique numbers

C Autocomplete feature

D Simple key-value lookup

Autocomplete requires fast prefix search, which Trie supports well.

What does a Trie node typically represent?

A A character in a string

B A whole string

C An integer value

D A hash code

Each Trie node represents one character in the stored strings.

Explain why a Trie is better than a hash map for prefix-based string searches.

Think about how strings are stored and searched.

Describe a real-world example where using a Trie is more efficient than a hash map for strings.

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