If you want to develop applications and become a software engineer, there are a lot of resources that you would have to learn before sitting for your first technical interview. However, it should be noted that developers should solely focus on the concept of data structures. Most beginners believe that knowledge of basic data structures wouldn’t be useful in their journey and they should only need to learn higher- order concepts of technology.
On the contrary, the reality is that learning the basic data structures is essential and for everyone who is aiming to build efficient as well as useful applications. In the world of computer science, there are numerous data structures and all of them are important in order to become a good software engineer. However, it is extremely important to have the knowledge of at least four types of basic data structures. Also, it not enough to know of these data structures, instead developers should have the knowledge of the applications of some of these basic data structures.
In this blog, we discuss the importance of data structure, why you should learn them and the 4 most basic data structures that are important and every beginner and even new software developers should know. We would begin this blog by understanding what exactly data structures are then continue with our compilation of four most important data structures. Let’s get started!
What are Data Structures?
You must have heard about how data has emerged to be the most important resource in the IT industry. No matter, what domain are you in or in which profile, you would have to work with data in various different forms. When it comes to data, one important thing is the container in which they are stored. In computer science, data structures are those containers which store data in a specific format. Hence, data structures have specific qualities that makes them different from other data structures.
Now that we have understood the meaning of data structure, it’s time we have a look at some of the most important data structures that you as a novice learner or a beginner as a software developer should know and understand their application. Remember, these data structures also help you to build efficient IT solutions. Let’s get started with our list of essential data structures.
The first one in our list is Arrays. They are one of the basic and maybe that’s why they are the most commonly used data structures. Arrays are also used to implement advanced Data structures like Queues and Stacks. Now, this was a quick introduction to arrays. Let’s get into the details, scratch the surface to know more about arrays.
In arrays, the location or position of each element in the array is denoted by a positive integer, usually starting from zero, known as the indexes or zero- based indexing.
In computer science, the array data structure is usually of two types. There is a one-dimensional array and a multi-dimensional array. Let’s understand each of these types in a bit more detail. To start with the types of arrays, one-dimensional arrays are basically linear type of arrays. On the other hand, multi-dimensional arrays are nested arrays.
There are some basic operations that can be done on arrays. For example, there can be a ‘Get’ operation, where you can fetch the array element at a particular index. Other than this, there can be an ‘Insert’ and ‘Delete’ option in which the user can insert an element or remove an element respectively at the given index in the array. You can also find the Length of an array by knowing the number of elements. You can always update the value of an element at the given index in array as well as traverse the array or search an element by looping through the array or using specific algorithms.
Arrays might seem like a simple, basic data structure. However, they have varied usage in the world of computer science. They also form the basis of more advanced data structures like stacks, queues among others. They are very easy to use and hence they are generally used for the simple storage of data. Other than that, this data structure is used to implement different sorting algorithms.
Next important data structure is linked list. A linked list is made up of elements called nodes. It is a linearly sequential data structure. Linked lists are made up of various nodes connected to each other. A node is a simple object that stores data along with storing the memory address of the next node in the list. Hence, a node contains the data value and the address of its neighbour. The structure of a linked list is such where each node is chained or connected to the other in the list. In programming, there are mainly three types of linked lists. They are Singly linked list, Doubly linked list and circular linked list. Let’s comprehend each of them in detail. Singly linked list is the normal kind of linked list in which the traversal of items can be done in one direction only. On the other hand, a doubly linked list consists of nodes that have an additional pointer which contains the address of the previous node. Hence, doubly linked list can be traversed in both the directions. Circular linked list is a type in which the previous pointer of the head of the linked list points to the tail and the next pointer of the tail points again to the head.
These were the most basic types of linked list in programming. Now, it’s time we look at some common operations in linked list. Majority of them are same as in arrays, however, the implementation is quite different in Linked list. For example, a node to the list can be inserted based on the required location such as the head or tail. The deletion can be done in the same manner. You can also traverse, display, search or update elements from the linked list.
There are also some diverse and comprehensive applications of linked lists. Like arrays, linked list can be used to create advanced data structures like queues, stacks, and also graphs. Other than that, linked list is utilised in image slideshows also as each and every image is linked to the next one. This data structure is also used in operating systems and in in dynamic memory.
Next data important data structure that you should definitely learn is stack. Like the other two data structures that we discussed, stack is also a linear data structure. Stacks are created on the base of either arrays or linked lists. When it comes to stacks or queues, there is a certain sequence of insertion and deletion of elements. In stack, the principle followed is Last-In-First-Out (LIFO). It means that the last element to get inserted in a stack, will be the first to get deleted. This data structure actually resembles stack in real life, for example, a stack of books on a table.
The basic operations that can be done on a stack are Push, Pop, Peek and isEmpty. Push, as the name suggests, inserts an element at the top of the stack and the pop operation removes the element from also the top of the stack. The two operations Peek and isEmpty returns the element at the top of the stack and checks whether the stack is empty or not respectively.
The various applications of stacks lie in browser navigation history and also is used in the implementation of recursion.
When you are done with all the basic data structures like arrays, linked lists, stacks and queues, you should move to advanced data structures like graphs and trees. In this segment we are going to talk about graphs. In programming, graphs are basically relative nodes, also called vertices, that are connected to each other. An edge is a pair which indicates that a node or a vertex x is connected to another node or vertex y. Usually, an edge indicates a value of either weight or cost.
In graphs, the number of edges in the graph is known as its size and the number of vertices in the graph is the order of the graph. In computer science, there are two types of graphs differentiated by the direction of the path between two vertices. The two graphs are directed graph and undirected graph. In a directed graph, all edges have directions that indicates their starting and ending vertex in the graph. On the other hand, Undirected graphs have edges with no directions and hence you can traverse it from any direction.
The algorithms commonly used in traversing a graph Breadth First Search or BFS and Depth First Search or DFS techniques. In BFS, the shortest path in a graph is found out using a technique based on vertices. The DFS algorithm is based on edges.
In a graph, a user can add a vertex and an edge between two vertices. The vertices can also be displayed in a graph and the total cost of a path can also be calculated by traversing it. A graph also represents the flow of computation and is used in resource allocation by the operating system. Popular use of graphs in the implementation of friend suggestion algorithms used by popular social media handles and also in Google Maps where it is used in the calculation of the shortest path between two locations.
Arrays, Linked List, Stack and Graph are the most basic data structures that every beginner in the IT industry should learn. As mentioned above, you should not only know the basics of these data structure but should also be well versed with their implementation and application.
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