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Classification of Data Structures

 Data structures can be broadly classified into two categories:

A. Linear Data Structures

These structures arrange data elements sequentially.

  • Arrays:
    A fixed-size collection of elements stored in contiguous memory. Arrays allow fast random access but have limitations in dynamic resizing.

  • Linked Lists:
    Consist of nodes where each node contains data and a pointer to the next node. Variants include:

    • Singly Linked List: Each node points to the next node.

    • Doubly Linked List: Nodes have pointers to both the next and previous nodes.

    • Circular Linked List: The last node points back to the first node, forming a circle.

  • Stacks:
    Data structures that work on the LIFO principle. Used for function call management, expression evaluation, and backtracking algorithms.

  • Queues:
    Operate on the FIFO principle. Queues are vital in scenarios like task scheduling, buffering, and breadth-first search (BFS) in graphs.

B. Non-Linear Data Structures

These structures do not store data in a sequential order.

  • Trees:
    Hierarchical structures with a root node and child nodes. Common types include:

    • Binary Trees: Each node has at most two children.

    • Binary Search Trees (BST): A binary tree with ordered nodes that facilitate quick search, insertion, and deletion.

    • Balanced Trees (e.g., AVL Trees, Red-Black Trees): Self-balancing trees that maintain a low height for efficient operations.

    • Heaps: A specialized tree-based structure used in priority queues.

  • Graphs:
    Consist of vertices (nodes) and edges (connections). Graphs can be directed or undirected and are used in modeling networks, social connections, and transportation systems. They are represented using:

    • Adjacency Matrix: A 2D array where each cell indicates the presence or absence of an edge.

    • Adjacency List: A collection of lists where each list contains the neighbors of a vertex.

  • Hash Tables:
    Use a hash function to map keys to indices in an array, enabling near constant-time data retrieval. They are widely used in implementing associative arrays, caching, and database indexing.

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