What s so hard about the data structure? What exactly is data structures learning

1) Can't accept the way it's described. The description of data structures is mostly in the form of abstractions, and we are used to using natural language expressions, which makes it difficult to accept the abstract expressions of data structures. More than one student asked me, what exactly is the type of "elemtype" in the book?

How often does the runtime prompt an error. It means "element type", but in this way, you can write whatever type you need, e.g. int. int. Such an expression will make many people feel devastated.

2) Don't know what it's for. Although many people learn data structures, they serve different purposes. Some people are coping with exams, some people need to participate in algorithm competitions, and many people don't know what the use of learning data structures is, and they are confused to read books, do questions, and take exams.

3) You don't appreciate the beauty of it. Due to the influence of various factors such as teaching materials and teachers, many students do not realize the wonders of data structure processing data, and are often anxious about not being able to learn.

What is the difficulty of data structure? Data structure refers to the set of data elements that have one or more relationships with each other and the relationship between the data elements in the set to form the final final, for the students who don't have time to see my ** simple summary two:

1. Know what it is, but also know why it is.

2. The data agency is the foundation of the algorithm, and the two cannot be separated.

Many textbooks talk about data structures, such as "linked lists" and "binary trees", what does the data structure look like, how to insert, how to delete, how to find, everything is said, but why do we need such a data structure? Don't talk about it! Or ...... in one goThis is very, very irresponsible!

Fei Ge was learning data structures at that time, and this point killed me. Very later, I don't know if it's ** looking at a sentence and picking up a paragraph in the west, "Oh, the linked list is for memory management!" "The stack is convenient for function calls" and "The binary tree is the index of the database......".In this way, these things are strung together bit by bit, and the world of data structures suddenly opens up.

To learn, you must know the purpose of learning and the meaning of learning, so that you can better persevere. It's like walking, blindfolded, and letting the person next to you tell you "three steps forward, two steps to the left, and ten steps to the right", think about it, how many people can survive this pattern? It's better to tell him at the beginning, "Let's go today, follow me!"

Looks like it could come a little more?

I talked about why I teach, maybe the students are more concerned about how to learn.

In fact, what I have always opposed is the supremacy of "data structures and algorithms" (and I also oppose the supremacy of "academic qualifications"), pay attention to the word "supremacy". For example, I hate the saying, "If you don't learn data structures and algorithms, you'll be a code animal for the rest of your life." It's really annoying, even if I learned a little bit myself.

There is no distinction between high and low knowledge.

There are always some people who think that there is a "core" technology that can't work without it - but I'm telling you, you can't do it without any technology.

Just a little more:

Data structures and algorithms, how to learn, depends on your interests. In fact, there is no end to learning, as long as you do your best, you can learn**, there is no problem. With the development of computers today, in fact, a large number of packages have been highly abstracted, and we as programmers do not necessarily have to build wheels.

In fact, it is already great to be able to use other people's wheels well and be a so-called good code farmer. The definition is a little stricter, and many, many program apes are not even "qualified".

Of course, you say, I'm particularly interested in this thing......That's okay, pan him! Isn't it? However, give a small piece of advice, don't make any sense of superiority.

It's not necessary, but also pull the hatred value, the key point, which is likely to make you narrow and limit your vision: in addition to data structures and algorithms, there are many, many interesting and challenging things.

There's a lot of data, it's complicated.

Extract useful data from a sea of data.

Frameworks are needed. There are data classification, statistics, collection, extraction, and retrieval methods.

is the data that is useful.

The difficulty is in the dll, it should not be difficult to write the output, the handle structure and objects are in the form of sets, the link library may be slightly difficult, and it also has to follow the network protocol and serial parallel port connection instructions.

I think data structures are the way computers store and organize data. A data structure is a collection of data elements that have one or more specific relationships with each other. In general, the structure of data is often related to efficient retrieval algorithms and indexing techniques.

Research objects: 1. The logical structure of data: refers to the data structure that reflects the logical relationship between data elements, where the logical relationship refers to the antecedent relationship between data elements, and has nothing to do with their storage location in the computer.

The logical structure includes:1The elements in the collection data structure have no relationship with each other except for the interrelationship of "belonging to the same set"; 2.

Elements in a linear structure data structure have a one-to-one interrelationship; 3.The elements in the tree structure data structure have a one-to-many interrelationship; 4.Elements in a graph structure data structure have many-to-many interrelationships.

2. Physical structure of data: refers to the form in which the logical structure of data is stored in the storage space of the computer. The physical structure of data is the representation (also known as an image) of the data structure in a computer, which includes the in-machine representation of the data element and the in-machine representation of the relationship.

Since there are many kinds of implementation methods, such as order, link, index, hash, etc., a data structure can be represented as one or more storage structures. In-camera representation of data elements (imaging method): Data elements are represented by a bit string of binary bits (bits).

This bit string is often referred to as a node. When a data element consists of several data items, the sub-bit strings corresponding to each data item in the bit string are called data fields. As such, a node is an in-machine representation (or in-machine image) of a data element.

In-camera representation of relationships (imaging method): In-machine representations of relationships between data elements can be divided into sequential and non-sequential images, and two storage structures are commonly used: sequential and chained.

Sequential images represent logical relationships between data elements by their relative positions in memory. A non-sequential image uses a pointer that indicates where the element is stored to represent the logical relationships between data elements. 3. Calculation of data structures.

Therefore, these are all things that the average person cannot grasp.

I think the reason why the data structure is difficult is because it is a kind of virtualization, because it is virtual, it is more difficult, because the data is difficult to figure out, and the data is a data organization calculated by a very complex calculation method, so it will be more difficult.

Personally, I think that the difficulty of data structure lies in its abstract thinking, structural thinking and data analysis ability, which require strong imagination to be able to complete, requiring people who are very sensitive to numbers and have a relatively high IQ to be competent.

The main learning of data structure: the method of using computers to realize data organization and data processing; With the continuous expansion of computer applications, a variety of complex data structures are used in the design of both system software and application software.

A good program is nothing more than choosing a reasonable data structure and a good algorithm, and the choice of a good algorithm largely depends on the data structure used to describe the actual problem, so if you want to write a good program, you must have a solid grasp of the data structure.

The definition of a data structure is as follows:

Data people use textual symbols, data symbols, and other prescribed symbols to abstractly describe things and activities in the real world. From a computer's point of view, data is a collection of all symbols that can be entered into a computer and processed by a computer.

Data Element: An "individual" in a data set, which is the basic unit of data; Data structure: refers to data and the relationship between them, which can be regarded as a collection of data elements that have a specific relationship with each other, so a data structure can be regarded as a collection of data elements with structure.

The data structure includes the following aspects: The logical structure of data refers to the logical relationships between data elements. For example, in a table; The order of the records reflects the logical relationship between the data elements, and the order in which the elements in an array are arranged is also the logical relationship between the data elements.

Data structure is a course for engineering computer majors, which mainly includes: computer science and technology, software engineering, network engineering, information security, Internet of Things engineering, digital media state rock mass technology, intelligent science and technology, spatial information and digital technology, electronic and computer engineering, data science and big data technology, cyberspace security, new technology, film production, security technology, service science and engineering, virtual reality technology, blockchain engineering, cryptography science and technology.

Supplementary Materials: The practical teaching (i.e., computer-based experiments) of data structure course design are divided into three categories: basic, comprehensive and design. Basic (i.e., knowledge verification) experiment questions are mainly used to consolidate classroom knowledge and realize the simple application of Mini Programs.

Comprehensive and design experiment questions belong to the big homework, which describes the whole process from modeling to demodulation to complete the design experiment problem, that is, the experimenter should complete it independently: the abstraction of the problem, the extraction of data, the organization of data, the confirmation of the data structure (logical structure), algorithm design, the storage form of data (physical structure), programming implementation, program debugging and testing and other steps.