
Data Structures and Algorithms (DSA) Tutorial
数据结构和算法 (DSA) 教程
数据结构和算法 (DSA) 是任何编程语言的两个重要方面。每种编程语言都有自己的数据结构和不同类型的算法来处理这些数据结构。
数据结构用于组织和存储数据,以便在执行数据操作时以有效的方式使用它。
算法是一个循序渐进的过程,它定义了一组要按特定顺序执行的指令,以获得所需的输出。算法通常是独立于底层语言创建的,即一个算法可以用多种编程语言实现。
几乎每个企业应用程序都以某种方式使用各种类型的数据结构。因此,作为一名程序员,数据结构和算法是日常编程中非常重要的方面。
数据结构是一种安排数据的特殊方式,以便可以将其保存在内存中并检索以供以后使用,而算法是解决已知问题的一组步骤。数据结构和算法在计算机科学的背景下缩写为 DSA。
本教程将让您对数据结构有很好的理解,以了解企业级应用程序的复杂性以及算法和数据结构的需求。
为什么要学习数据结构和算法 (DSA)?
随着应用程序变得越来越复杂和数据丰富,应用程序现在面临三个常见问题。
数据搜索 − 考虑一家商店的 100 万 (106) 件商品的库存。如果应用程序要搜索某个项目,则每次都必须在 100 万 (106) 个项目中搜索一个项目,这会减慢搜索速度。随着数据的增长,搜索速度会变慢。
处理器速度 − 处理器速度虽然非常高,但如果数据增长到十亿条记录,速度就会受到限制。
多个请求 − 由于数千名用户可以同时在 Web 服务器上搜索数据,因此即使是快速的服务器也会在搜索数据时失败。
为了解决上述问题,数据结构可以派上用场。可以以这样的方式将数据组织在数据结构中,使得可能不需要搜索所有项目,并且可以几乎立即搜索所需的数据。
如何开始学习数据结构和算法(DSA)?
学习DSA的基本步骤如下:
步骤1 - 学习时间和空间复杂度
时间和空间复杂度是执行代码所需时间量(时间复杂度)和执行代码所需空间量(空间复杂度)的度量。
步骤2 - 学习不同的数据结构
在这里,我们学习不同类型的数据结构,如数组、堆栈、查询、链表等。
步骤3 - 学习不同的算法
一旦您对各种数据结构有了很好的理解,您就可以开始学习相关算法来处理存储在这些数据结构中的数据。这些算法包括搜索、排序和其他不同的算法。
Applications of Data Structures & Algorithms (DSA)
From the data structure point of view, following are some important categories of algorithms −
Search − Algorithm to search an item in a data structure.
Sort − Algorithm to sort items in a certain order.
Insert − Algorithm to insert item in a data structure.
Update − Algorithm to update an existing item in a data structure.
Delete − Algorithm to delete an existing item from a data structure.
The following computer problems can be solved using Data Structures −
- Fibonacci number series
- Knapsack problem
- Tower of Hanoi
- All pair shortest path by Floyd-Warshall
- Shortest path by Dijkstra
- Project scheduling
Who Should Learn DSA
This tutorial has been designed for Computer Science Students as well as Software Professionals who are willing to learn data Structures and Algorithm (DSA) Programming in simple and easy steps.
After completing this tutorial you will be at intermediate level of expertise from where you can take yourself to higher level of expertise.
DSA Online Editor & Compiler
In this tutorial, we will work with data structures and algorithms in four different programming languages: C, C++, Java, Python. So, we provide Online Compilers for each of these languages to execute the given code. Doing so, we are aiming to compromise the need for local setup for the compilers.
#include <stdio.h> int main(){ int LA[3] = {}, i; for(i = 0; i < 3; i++) { LA[i] = i + 2; printf("LA[%d] = %d \n", i, LA[i]); } return 0; }
Output
LA [0] = 2 LA [1] = 3 LA [2] = 4
#include <iostream> using namespace std; int main(){ int LA[3] = {}, i; for(i = 0; i < 3; i++) { LA[i] = i + 2; cout << "LA[" << i <<"] = " << LA[i] << endl; } return 0; }
Output
LA [0] = 2 LA [1] = 3 LA [2] = 4
public class ArrayDemo { public static void main(String []args) { int LA[] = new int[3]; for(int i = 0; i < 3; i++) { LA[i] = i+2; System.out.println("LA[" + i + "] = " + LA[i]); } } }
Output
LA [0] = 2 LA [1] = 3 LA [2] = 4
LA = [0, 0, 0] x = 0 for x in range(len(LA)): LA[x] = x+2; print("LA", [x], " = " , LA[x])
Output
LA [0] = 2 LA [1] = 3 LA [2] = 4
Prerequisites to Learn DSA
Before proceeding with this tutorial, you should have a basic understanding of C programming language, text editor, and execution of programs, etc.
DSA Online Quiz
This Data Structures Algorithms tutorial helps you prepare for technical interviews and certification exams. We have provided various quizzes and assignments to check your learning level. Given quizzes have multiple choice type of questions and their answers with short explanation.
Following is a sample quiz, try to attempt any of the given answers:
Q - A complete graph can have
Answer : B
Explanation
At maximum, a complete graph can have nn - 1 spanning trees.
Start your online quiz Start Data Structures Algorithms Quiz.
DSA Jobs and Opportunities
Professionals in DSA are in high demands as more and more organizations rely on them to solve complex problems and make data-driven decisions. You can earn competitive salaries, and the specific pay can vary based on your location, experience, and job role.
Many top companies are actively recruiting experts in DSA, and they offer roles such as Software Engineer, Data Scientist, Machine Learning Engineer, and more. These companies need individuals who can solve complex problems, analyse data, and create algorithms to drive their business forward. Here is the list of few such companies −
- Amazon
- Microsoft
- Apple
- Adobe
- JPMorgan Chase
- Goldman Sachs
- Walmart
- Johnson & Johnson
- Airbnb
- Tesla
These are just a few examples, and the demand for DSA professionals is continually growing across various sectors. By developing expertise in these areas, you can open up a wide range of career opportunities in some of the world's leading companies.
To get started, there are user-friendly tutorials and resources available to help you master DSA. These materials are designed to prepare you for technical interviews and certification exams, and you can learn at your own pace, anytime and anywhere.
Frequently Asked Questions about DSA
There are many Frequently Asked Questions (FAQs) on Data Structures and Algorithms due to the complex nature of this concept. In this section, we will try to answer some of them briefly.
A data structure is a collection of similar or different data types, and is used to store and modify data using programming languages. And, an algorithm is defined as a set of instructions that must be followed to solve a problem.
Data Structures and Algorithms is a study of such data structures and the algorithms that use them.
The best programming language to work with data structures is C++, due to its efficiency and abundant resources for data structures. Despite that, any programming language can be the best pick to work with data structures if you are fluent in it.
Here are the summarized list of tips which you can follow to start learning Data Structures.
- Follow our tutorial step by step from the very beginning.
- Read more articles, watch online courses or buy reference books on Data Structures to enhance your knowledge.
- Try to execute a small program using data structures in any programming language to check your knowledge in these concepts.
A datatype is a type of value a variable holds. These values can be numeric, string, characters, etc. An array is defined as a collection of similar type of values stored together. Hence, it is more likely to be a data structures storing values of same datatype.
Data Structures organize the data used in algorithms. They are the foundation of computations performed using algorithms. Hence, learning data structures is recommended first, as it becomes easier to understand the concept of Algorithms with all the prior knowledge.
Not only in software development, but we can observe the use of data structures in our day-to-day life as well. For instance, piling up plates and removing them one-by-one is the simpler example on how stack data structure organizes its data. Similarly, queueing up to buy movie tickets has the same mechanism as inserting and deleting the data from a queue.
In software development, developing navigation maps using graph data structure is also a common real life application.
Machine Learning and Deep Learning work with mathematical computations and large sets of data. Organizing this data properly becomes crucial in order to process these data-sets for training and deploying suitable models on them. Hence, having a deep knowledge in Data Structures and Algorithms is important while working with Machine Learning and Deep Learning.
A datatype defines the type of value stored in a variable. This decides the type of operations performed and functions called on these values. Whereas, a data structure is a collection of similar or different types of data, which is used to organize and manipulate data in a program.