There are several types of data structures commonly used in programming. Each data structure has its own characteristics and is suited for specific types of operations and data organization. Here are some of the most commonly used data structures:
Arrays: An array is a collection of elements of the same type, stored in contiguous memory locations. It allows for efficient access to elements using their indices. Arrays have a fixed size, and elements can be accessed using constant time complexity.
Lists: Lists are dynamic data structures that can store elements of different types. They can grow or shrink dynamically as elements are added or removed. Lists usually provide operations for insertion, deletion, and retrieval of elements.
Stacks: A stack is a Last-In-First-Out (LIFO) data structure. Elements can be added or removed only from one end, called the top. The most recently added element is the first one to be removed.
Queues: A queue is a First-In-First-Out (FIFO) data structure. Elements are added at one end, called the rear, and removed from the other end, called the front. The first element added is the first one to be removed.
Linked Lists: A linked list is a collection of nodes, where each node contains data and a reference to the next node. Unlike arrays, linked lists do not require contiguous memory allocation and can dynamically grow or shrink.
Trees: Trees are hierarchical data structures with a root node and child nodes. Each node can have zero or more child nodes. Trees are used for organizing hierarchical relationships between data elements.
Graphs: Graphs consist of a set of vertices (nodes) connected by edges. They are used to represent relationships between entities and are widely used in network analysis, social networks, and routing algorithms.
Hash Tables: A hash table is a data structure that uses a hash function to map keys to values. It provides constant-time average case for insertion, deletion, and retrieval operations.
These are just a few examples of data structures commonly used in programming. Each data structure has its own strengths and weaknesses, and the choice of data structure depends on the specific requirements of the problem at hand.
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