Prefix Search Using Trie in DSA C++ - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is a Trie data structure?

A Trie is a tree-like data structure used to store a dynamic set of strings where keys are usually strings. Each node represents a character, and paths from the root to nodes represent prefixes of stored words.

beginner

How does a Trie help in prefix search?

A Trie allows quick prefix search by following the path of characters from the root node. If the prefix exists, the search reaches the node representing the last character of the prefix, enabling retrieval of all words starting with that prefix.

intermediate

What is the time complexity of searching a prefix in a Trie?

The time complexity is O(m), where m is the length of the prefix. This is because the search follows the path character by character without scanning all stored words.

beginner

Explain the role of the 'isEndOfWord' flag in a Trie node.

The 'isEndOfWord' flag marks if a node corresponds to the last character of a valid word stored in the Trie. It helps distinguish between prefixes and complete words during search and retrieval.

beginner

What happens if a prefix is not found in a Trie during search?

If the prefix path does not exist in the Trie, the search stops early, indicating no words start with that prefix. This makes prefix search efficient by avoiding unnecessary checks.

What does each node in a Trie represent?

A A character of a string

B A whole word

C An integer value

D A prefix length

Each node in a Trie represents a single character of the stored strings.

What is the main advantage of using a Trie for prefix search?

A Sorts words alphabetically

B Faster search by following character paths

C Stores only numbers

D Uses less memory than arrays

Trie allows fast prefix search by following the path of characters without scanning all words.

What does the 'isEndOfWord' flag indicate in a Trie node?

A Node has no children

B Node is the root of the Trie

C Node is the last character of a stored word

D Node stores a prefix length

'isEndOfWord' marks the end of a valid word in the Trie.

If a prefix is not found in a Trie, what happens?

A Search stops early, no words with that prefix

B All words are returned

C Trie deletes the prefix

D Search continues to the end

Search stops early if prefix path does not exist, indicating no matching words.

What is the time complexity of prefix search in a Trie for prefix length m?

A O(m * n)

B O(n)

C O(log n)

D O(m)

Prefix search time depends only on prefix length m, so it is O(m).

Describe how a Trie is used to perform prefix search.

Think about how you follow letters step-by-step in a tree.

Explain why prefix search in a Trie is efficient compared to scanning all words.

Consider how you find words starting with 'app' without checking every word.