The data structure includes three aspects: linear structure, tree structure and graphic structure. Detailed introduction: 1. Linear structure is one of the simplest and most common data structures. There is a one-to-one relationship between data elements in the linear structure, that is, each element has only one direct predecessor and one direct successor. The linear structure Common implementation methods include arrays, linked lists, stacks and queues; 2. The tree structure is a non-linear data structure, which consists of nodes and edges. There is a one-to-many relationship between the nodes in the tree structure, that is, each A node can have multiple child nodes and so on.
The operating system for this tutorial: Windows 10 system, DELL G3 computer.
Data structure is an important concept in computer science, which involves the ways and methods of organizing and storing data. Data structure can be divided into three aspects: linear structure, tree structure and graph structure.
First of all, linear structure is one of the simplest and most common data structures. There is a one-to-one relationship between data elements in a linear structure, that is, each element has only one direct predecessor and one direct successor. Common implementations of linear structures include arrays, linked lists, stacks and queues. An array is a contiguously stored data structure whose elements can be accessed by index. A linked list is a non-contiguous data structure in which elements are linked together through pointers. The stack is a last-in-first-out (LIFO) data structure that only allows insertion and deletion operations at one end. A queue is a first-in-first-out (FIFO) data structure that allows insertion operations at one end and deletion operations at the other end.
Secondly, the tree structure is a non-linear data structure, which consists of nodes and edges. There is a one-to-many relationship between nodes in the tree structure, that is, each node can have multiple child nodes, but each child node can only have one parent node. Common implementations of tree structures include binary trees, heaps, and Huffman trees. A binary tree is a tree structure in which each node has at most two child nodes. A heap is a special binary tree that satisfies the heap property, that is, the value of a parent node is always greater than or equal to (or less than or equal to) the value of its child node. Huffman tree is a tree structure used for data compression, which achieves efficient compression of data by encoding less frequent characters into shorter binary codes.
Finally, the graph structure is a non-linear data structure composed of nodes and edges, and the relationship between nodes can be many-to-many. Common implementations of graph structures include adjacency matrices and adjacency lists. An adjacency matrix is a two-dimensional array used to represent relationships between nodes. An adjacency list is a linked list array, each node corresponds to a linked list, and the linked list stores the nodes adjacent to the node. Graph structures are often used to describe complex relationships such as networks and social relationships.
To sum up, the data structure includes three aspects: linear structure, tree structure and graphic structure. Understanding and mastering different types of data structures is of great significance for solving practical problems and optimizing algorithms, and they have wide applications in computer science and software engineering.
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