Design & Analysis of Algorithms - Vol 2 | 14. Search Trees by Abraham | Learn Smarter
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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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Sections

  • 1

    Search Trees

    This section introduces Search Trees as a data structure essential for managing and retrieving data efficiently, particularly in situations requiring ordered access.

    Learning Practice

  • 1.1

    Introduction To Search Trees

    This section introduces search trees, focusing on their application in prioritizing flight requests by managing arrival and departure times effectively.

    Learning Practice

  • 1.2

    Use Case: Air Traffic Control

    The section discusses the use of search trees as data structures in air traffic control for managing landing and takeoff requests based on their timing.

    Learning Practice

  • 1.3

    Priority Queue And Min Heap

    This section introduces the concept of priority queues and min heaps, exploring their applications in managing requests based on priority, specifically in situations like air traffic control.

    Learning Practice

  • 1.4

    Minimum Separation Requirement

    The section discusses the concept of ensuring minimum separation between events in algorithm design, particularly focusing on search trees and priority queues.

    Learning Practice

  • 1.5

    Predecessor And Successor

    This section introduces the concept of predecessors and successors in the context of search trees, particularly focusing on their importance in managing time-sensitive processes, such as air traffic control.

    Learning Practice

  • 1.6

    Data Structures Comparison

    This section discusses the importance of search trees in algorithm design, focusing on their functionality and efficiency compared to other data structures.

    Learning Practice

  • 1.7

    Binary Search Trees

    This section introduces Binary Search Trees (BSTs), a type of data structure that allows efficient searching, insertion, and deletion of values based on a specific ordering property.

    Learning Practice

  • 1.8

    Binary Tree Basics

    This section introduces binary trees and binary search trees, emphasizing their structure and properties.

    Learning Practice

  • 1.9

    Node Terminology

    This section introduces search trees, focusing on node terminology and their roles in data structures, particularly in binary search trees.

    Learning Practice

  • 1.10

    Binary Search Tree Properties

    This section explores the properties of Binary Search Trees (BSTs) and their role in optimizing search operations within data structures.

    Learning Practice

  • 1.11

    In-Order Traversal

    In-order traversal is a method of visiting each node in a binary search tree to list the values in sorted order.

    Learning Practice

  • 1.12

    Searching In Binary Search Trees

    This section discusses binary search trees and their operations, focusing on the efficiency of searching, inserting, and deleting nodes.

    Learning Practice

References

ch39 part a.pdf

Class Notes

Memorization

What we have learnt

  • Binary search trees allow f...
  • The constraints of binary s...
  • In-order traversal of a bin...

Final Test

Revision Tests