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 When dealing with strings—like searching for words in a dictionary, building autocomplete systems, or implementing spell checkers—efficiency matters. One powerful tool for such tasks is the Trie (pronounced “try” ), also known as a prefix tree . In this post, we’ll explore what a Trie is, why it’s useful, how it works, and where you can apply it. What is a Trie? A Trie is a tree-like data structure designed for storing and retrieving strings efficiently. Unlike a binary search tree (BST), where nodes represent keys, each node in a Trie represents a single character of a string . For example, consider inserting the words: cat , car , apple and ant . The Trie would look like this: Notice how the common prefix "ca" is stored only once, making the Trie memory-efficient when handling large sets of overlapping words. Key Properties of a Trie Nodes represent characters : Each edge corresponds to a letter in a string. Root node is empty : It represents the starting poin...