14. Search Trees
Search Trees are a crucial data structure for managing requests based on priority, particularly in time-sensitive scenarios like air traffic control. By leveraging the properties of binary search trees, operations such as insertion, deletion, and searching can be optimized to logarithmic time complexities, allowing for efficient management of event requests. The chapter details the structure of binary search trees, their operational efficiency, and practical implementations in scenarios requiring ordered data retrieval.
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What we have learnt
- Binary search trees allow for logarithmic time complexity in insertion, deletion, and search operations.
- The constraints of binary search trees ensure that nodes are arranged such that all left descendants are smaller and all right descendants are larger than the parent node.
- In-order traversal of a binary search tree results in a sorted sequence of values.
Key Concepts
- -- Binary Search Tree (BST)
- A type of data structure where each node has a maximum of two children, with left children being less than the parent node and right children being greater.
- -- InOrder Traversal
- A method of traversing a binary search tree where the left subtree is visited first, followed by the parent node, and then the right subtree, resulting in values being printed in sorted order.
- -- Heap
- A specialized tree-based structure that satisfies the heap property where the parent node's value is either greater than or equal to or less than or equal to that of its children, depending on whether it is a max heap or min heap.
- -- Predecessor and Successor
- In the context of a binary search tree, the predecessor is the largest value that is less than a given node value, and the successor is the smallest value that is greater.
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