How to Design a Trie (Prefix Tree)?

Design and implement a Trie (Prefix Tree) data structure that efficiently stores and retrieves strings. The Trie should support insert(word), search(word) for exact matches, startsWith(prefix) for prefix matching, autocomplete(prefix) to return all words with a given prefix, delete(word) to remove words, and countWordsWithPrefix(prefix) to count words sharing a prefix. The design should demonstrate understanding of tree structures, character-based edge traversal, prefix matching algorithms, DFS traversal for autocomplete, and efficient word deletion. Use our interactive playground to practice this problem with step-by-step guidance, UML diagram builder, and complete solutions in multiple programming languages.

What is Design a Trie (Prefix Tree)?

Design and implement a Trie (Prefix Tree) data structure that efficiently stores and retrieves strings. The Trie should support insert(word), search(word) for exact matches, startsWith(prefix) for prefix matching, autocomplete(prefix) to return all words with a given prefix, delete(word) to remove words, and countWordsWithPrefix(prefix) to count words sharing a prefix. The design should demonstrate understanding of tree structures, character-based edge traversal, prefix matching algorithms, DFS traversal for autocomplete, and efficient word deletion.

How to solve Design a Trie (Prefix Tree) in Easy difficulty?

This is a easy level Low Level Design problem. Practice with our interactive playground that provides step-by-step guidance, clarifying questions, UML class diagram builder, and complete solutions in Python, Java, C++, TypeScript, JavaScript, and C#.

What design patterns are used in Design a Trie (Prefix Tree)?

This problem uses the following design patterns: Trie, Prefix Tree, Tree Traversal, DFS, Composite Pattern, Strategy Pattern. Learn how to apply these patterns with our interactive practice playground.

Design a Trie (Prefix Tree) - Step-by-Step Guide with Solutions

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// Define key contracts here