🍊 Tries | Data Structures & Algorithms

#DataStructures #Algorithms #Trie #ComputerScience This video provides an introduction to the Trie, a special tree-based data structure that is highly optimized for storing and searching a large set of strings. Presented by Hayden Smith, this lecture explains the concept, structure, and performance of tries. 🌳 What is a Trie? A Trie (pronounced "try," from the word retrieval) is a tree structure where paths from the root downward spell out words or prefixes. Instead of storing a whole string in a node, the position of a node in the trie represents a prefix. Each node typically represents a single character and has links to its children, one for each possible next character in the alphabet. Nodes can be marked as "finishing" nodes to indicate that the path from the root to that node forms a complete word in the set. ⚡ The Advantage: Fast Lookups The primary benefit of using a trie is its incredibly fast performance for lookups and insertions. The time complexity for these operations is O(L), where L is the length of the string. This means the time it takes to find a word is dependent only on the length of that word, not on the total number of words stored in the trie. ⚙️ How Trie Operations Work Search: To find a word, you traverse the trie from the root, following the path of the word's characters. If you can trace the entire path and the final node is marked as a "finishing" node, the word exists. Insert: To add a word, you follow its path through the trie, creating new nodes as needed. The node corresponding to the last character of the word is then marked as a "finishing" node. 🧱 Trie Variations The basic trie structure can be very space-inefficient, as each node might need to store pointers for every character in the alphabet. To solve this, optimized versions exist, such as Compressed Tries (or Radix Trees), which compress non-branching chains of nodes to significantly reduce memory usage. View the full playlist: https://www.youtube.com/playlist?list=PLi2pCZz5m6GEftzPIxVH1ylwytux9WOGN