Binary trees are a fundamental data structure in computer science with various applications across multiple domains. A binary tree consists of nodes, where each node has at most two children, commonly referred to as the left and right child. This structure facilitates efficient searching, insertion, and deletion operations, particularly when implemented as a binary search tree (BST). In a BST, the left child of a node contains values less than the node's value, while the right child contains values greater than the node's value, allowing for fast retrieval of elements with average-case time complexity of O(log n). One common application of binary trees is in expression parsing and evaluation, where binary expression trees represent mathematical expressions with operators as internal nodes and operands as leaf nodes. This allows for easy evaluation of expressions by traversing the tree. Binary trees are also used to represent hierarchical data structures, such as organizational charts and file systems, where each node represents an entity, and child nodes represent sub-entities. Furthermore, binary trees can be employed in implementing priority queues through binary heaps, enabling efficient retrieval of the highest (or lowest) priority element. Understanding binary trees and their applications is essential for mastering data structures and algorithms, as they serve as a building block for many complex systems in computer science.