Data structures and algorithms, data structure Algorithms

Data structures and algorithms, data structure Algorithms
What is a data structure?

The data structure is divided into data and structure. Numbers, characters, graphics, and sounds are all data. The structure is divided into logical structure and storage structure. The logical structure is the abstract relationship between data. The storage structure is the storage of data in computer memory (memory, disk. Data structure studies how data is stored in computers. Data structures include arrays, stacks, binary trees, and hash tables.

What is an algorithm?

Algorithms are the process of processing a given problem in a computer. To put it bluntly, they process data in a data structure, such as sorting and searching data.

What is the relationship between data structures and algorithms?

The data processing process of a computer: Data Input --> Computer Processing-> data output
It is important to organize raw data and store it in a computer to facilitate space saving and computer processing. It is also important to select appropriate algorithms to improve the efficiency and reliability of solving problems, it cannot be discussed in isolation.
Algorithms can only play a role in an appropriate data structure. Different data structures affect algorithm selection and efficiency.
Some scientists concluded that algorithm + Data Structure = Program

What are the functions of data structures and algorithms?

After learning about the previous concepts, let's take a look at the application scenarios.
Real Data Storage:
Store physical and physical data outside the computer in the real world. For example, a personnel file records the information of a real person.
Programmer tools:
The chain table, stack, queue, and other structures are used as tools to simplify other operations.
Modeling the Real World:
Construct a model for the real world using a data structure. It is used to represent the routes and circuit connections between cities.
Get a general understanding of the features of the data structure:

Data Structure	Advantages	Disadvantages
Array	Fast insertion and quick access to subscripts	Slow query, slow deletion, fixed size
Ordered array	Faster than searching unordered Arrays	Slow insertion and deletion, fixed size
Stack	Back-to-first-out access	Slow access to other items
Queue	First-in-first-out access	Slow access to other items
Linked List	Fast insertion and Deletion	Slow Query
Binary Tree	Fast insertion, deletion, and search (such as balance between fruit trees)	Complex deletion Algorithms
Red-black tree	Insert, delete, and search are fast (the tree is always balanced)	Complex algorithms
2-4-4 trees	Insert, delete, and search are fast (the tree is always balanced). Similar trees are useful for disk storage.	Complex algorithms
Hash table	If the keywords are known, the access speed is extremely fast and the insertion speed is fast.	Slow deletion, unknown keywords, slow storage, insufficient disk space utilization
Heap	Fast insertion and deletion, fast access to the largest data item	Slow access to other data items
Figure	Real-world Modeling	Some algorithms are slow and complex.

In addition to arrays, the above are called abstract data structures (ADT ).