Unlocking Data Structures & Algorithms

A journey through data manipulation, optimization, and algorithmic thinking.

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Core Data Structures

Linked List

A linear data structure where elements are linked using pointers. Useful for dynamic memory.

Best for: Implementing stacks, queues, and managing dynamic data.

Doubly Linked List

Bidirectional linear structure for efficient forward/backward traversal. Each node has two pointers: One to the next node, and another to the node previous to it.

Best for: Undo/redo operations, browser history, music playlists.

Array

Indexed data collection for accessing sequential elements in contiguous memory. These elements have the same type.

Best for: Storing and accessing fixed-size data, image processing.

Stack

Follows the Last In First Out (LIFO) principle. Push adds to the top, pop removes the top element.

Best for: Function calls, expression evaluation, managing history.

Queue

Follows the First In First Out (FIFO) principle. Enqueue adds to the rear, dequeue removes the front element.

Best for: Task scheduling, print queue, managing requests.

Binary Search Tree

A tree where each node has at most two children, maintains sorted order. Search and insertion are quick O(log n).

Best for: Searching, sorting, and data indexing for retrieval.

Hash Table

Associative array to stores key-value pairs. Provides fast lookups (O(1) on average).

Best for: Implementing dictionaries and speeding up data retrieval.

Graph

Consists of nodes connected by edges, useful for modeling relationships. Can be directed or undirected.

Best for: Social networks, routing, web connections, recommendation systems.

B-Tree

Self-balancing tree optimized for disk storage, minimizes disk access. Good for large databases.

Best for: Database indexing, efficient file systems, large dataset storage.