26. Advanced Data Structures (e.g., Trees, Graphs)
Advanced data structures, including trees and graphs, are essential for efficient data manipulation as programs scale in complexity. This chapter delves into a variety of structures such as binary trees, binary search trees, heaps, tries, and graphs, exploring their properties, operations, and real-world applications. Understanding these structures enhances problem-solving capabilities in complex software development environments.
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What we have learnt
- Trees provide a hierarchical representation of data essential for applications like file systems and compilers.
- Graphs serve as a crucial framework for modeling complex relationships in applications ranging from social networks to navigation systems.
- Data structures like heaps and tries enhance operational efficiency in priority tasks and string searching respectively.
Key Concepts
- -- Binary Tree
- A tree structure where each node has at most two children, used in various applications for orderly data storage.
- -- Binary Search Tree (BST)
- A type of binary tree that maintains sorted order, allowing efficient search, insert, and delete operations.
- -- Heap
- A complete binary tree used primarily to implement priority queues, characterized by the hierarchical arrangement of elements.
- -- Trie
- A tree-based data structure optimized for storing and searching strings efficiently, commonly used in applications like autocomplete.
- -- Graph
- A non-linear data structure made up of vertices and edges, used to represent pairwise relationships in data.
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