Overview - Introductory Notes on Algorithms and Data Structures (1)

This article is the first study note of algorithm and data structure, and it will be updated continuously. Friends are welcome to read and learn. If there is something that I don’t understand or is wrong, please communicate

Introduction

In computer science and software development, algorithms and data structures are an important part of building a solid programming foundation. Whether you want to be a good programmer or stand out in interviews, mastering algorithms and data structures is essential. This article will introduce you to algorithms and data structures, explore their importance, and start learning them step by step.

What are Algorithms and Data Structures?

Discussing from the content of the program, a program mainly includes the following two aspects of information:

1. A description of the data . In the program, it is necessary to specify which data to use, the type of these data and the organizational form of the data. This is the data structure (data structure).
2. A description of the operation . That is, the steps that require the computer to operate are called algorithms .

Data is the object of operation, and the purpose of operation is to process the data to obtain the desired result. Therefore, the definitions and relationships of algorithms and data structures are as follows:

An algorithm is a series of steps or methods for solving a problem. In computer science, an algorithm is a series of instructions for solving a specific problem. Data structures are the ways in which data is organized and stored, and they define how the data is organized, manipulated, and accessed . Algorithms and data structures are closely related. Algorithms work on specific data structures. Excellent data structures can support efficient algorithm implementation.

The importance of algorithms and data structures

The famous computer scientist Nikiklaus Wirth proposed a formula: $$algorithm+data\; structure=Program$$ Although this view has always been quite controversial, it also indirectly illustrates the importance of algorithms. In fact, in addition to the above two main elements, a program should also be designed using a programming method and expressed in a certain computer language. Therefore,the four aspects ofalgorithm, data structure, programming methodandlanguage toolAmong these four aspects, algorithm is the soul, data structure is the processing object, language is the tool, and programming needs to adopt the appropriate method.

Learning algorithms and data structures can help us

1. Improve program performance: Excellent algorithms and data structures can significantly improve program performance. By choosing appropriate data structures and designing efficient algorithms, time and space complexity can be reduced, and program execution speed and resource utilization can be improved.

2. Solving complex problems: Algorithms and data structures provide the basis for solving complex computational problems. They help us design efficient solutions and optimize program execution.

3. Improve interview competitiveness: At present, almost all development positions in large factories and small and medium-sized factories require mastering algorithms and data structures! ! ! At present, the campus recruitment written test generally adopts the form of Online Judge, which is generally 20-30 multiple-choice questions + 2 programming questions, or 3-4 programming questions. And the algorithm is not only tested in the written test, but the interviewer will basically let the interviewer write the code on the spot. It can be seen that the company's requirements for students' coding ability are getting higher and higher. Armed with these basics, you'll be better able to demonstrate your analytical and problem-solving skills.

learning route

The following is a mind map for learning data structures and algorithms:

Common data structures and algorithms are as follows:

Common Data Structures

Array (Array) : It is a linear data structure that can store a group of elements of the same type and store them in sequential memory locations. The access speed of the array is fast, and the elements are directly accessed through the index, but the insertion and deletion operations are relatively slow.

Linked List : A linked list is also a linear data structure that consists of nodes, each node contains an element and a pointer to the next node. The insertion and deletion operations of the linked list are more efficient, but accessing the element at a specific position requires traversing the entire linked list.

Skip List (Skip List) : A data structure based on an ordered linked list for quickly finding elements. It speeds up the lookup operation of the linked list by adding a multi-level index layer. The jump table can realize fast insertion, deletion and search operations based on the ordered linked list.

Stack : The stack is a data structure with last-in-first-out (LIFO) characteristics, which can be pushed and popped. It only allows insertion and deletion at one end. Stacks are often used in scenarios such as function calls, expression evaluation, and bracket matching.

Queue : A queue is a data structure with first-in-first-out (FIFO) characteristics, which can perform enqueue and dequeue operations. It allows insertions at one end and deletions at the other. Queues are often used in scenarios such as task scheduling and breadth-first search.

Tree : A tree is a non-linear data structure consisting of nodes and edges. Each node can have zero or more child nodes, one of which acts as the root node. Common trees include binary tree, binary search tree, AVL tree, etc. Trees are commonly used in applications such as organizing data, searching, and sorting.

Heap : Heap is a complete binary tree data structure, which can be divided into maximum heap and minimum heap. In a max-heap, the value of the parent node is greater than or equal to the value of the child node; in a min-heap, the value of the parent node is less than or equal to the value of the child node. Heaps are often used to implement priority queues, sorting algorithms, etc.

Hash Table : Also called a hash table, it is a data structure that directly accesses data based on keywords (key values, Key). It maps keys to a fixed-size array index through a hash function for efficient insertion, deletion, and lookup operations.

Graph : A graph is a non-linear data structure composed of nodes and edges. Nodes represent entities, and edges represent relationships between nodes. Graphs can be used to solve problems such as network analysis and path search.

common algorithm

Sorting algorithms : such as bubble sort, insertion sort, selection sort, quick sort, merge sort, etc. These algorithms are used to arrange a set of elements into a specific order.

Search (find) algorithms : such as depth-first search, breadth-first search, binary search, etc. These algorithms are used to find specific elements in a set of data.

Graph theory algorithms : such as shortest path algorithm, minimum spanning tree algorithm, topological sorting, etc. These algorithms are used to solve related problems in graph structures.

Dynamic programming algorithms : such as knapsack problem, longest common subsequence, longest increasing subsequence, etc. These algorithms are used to solve multi-stage decision process optimization problems.

String matching algorithms : such as simple string matching, KMP algorithm, Boyer-Moore algorithm, etc. These algorithms are used to find the occurrence of a pattern string in a text string.

summary

The importance of algorithms and data structures is self-evident, and they provide key tools for solving complex problems and optimizing program performance. Learning common algorithms and data structures will help you better analyze and solve problems. Continuously learning and practicing algorithms and data structures can continuously improve your programming ability.

The next article will introduce how to measure the performance of the algorithm before introducing the commonly used data structures and commonly used algorithms in detail. It is being continuously updated...