Generally, we deal with a massive amount of data, but when it comes to handling data in the area of software development, several technologies are available. The goal is to determine which tool is most suited for our specific task. As a reminder, regardless of what programming language we start programming in, one of the initial concepts we encounter is data Structures, which we should be familiar with by now. Data Structures are objects that employ numerous methods to shape as well as structure data. A linked list is a data structure that may appear complicated initially, but the better you understand them, the more intriguing they may become. In this article, we will understand different applications of Linked List. So, let’s first start with the introduction of Linked List.

Basic Introduction to a Linked List

A linked list is continuous and sometimes also conferred as a dynamic data structure of connected nodes. Each node holds the data as well as the addresses of the subsequent nodes. Memory allocation occurs during runtime, it can efficiently perform operations such as insertion, append, and elimination without reorganizing the entire list; however, if we want to perform the same activities on an array that should allocate secured memory, its execution time will increase. As a result, when it involves memory and storage, linked lists are more critical than arrays. As an example,

Here you can see we have a head that contains the address of the first node, and in the first node, we have the address of the second node(next), and this pattern goes on until the next pointer is null. Null indicates that there is no node further this is the last node. So one thing must be clear that everything is connected here serially, but as an array, we cannot access anything in O(1) by just giving the position number , here we have to start from the beginning, and then we can travel to our desired node. You’ve probably seen a game of Treasure Hunt, whereby each clue contains information about the following clue. That is how a linked list works. Normally there are three types of linked lists singly, doubly, and circular.

Linked List Illustration

Let's look at how each linked list node is represented. Each node is made up of:

A piece of information
another node's address

In a struct, we encase either the information item and the subsequent node reference as follows:

struct node1 {
 int data_item; //this depicts the data value
struct node1 *next_address; //this contains the address of the next node
};

This was the very basic introduction to the linked list.

Application of linked list

1. Stacks Implementation: A linked list data structure can be used to create a stack data structure. When combined with a linked list, the Stack may hold enduring values. This means that the Stack included linked list operations for variable-size data. As a result, there is no need to fix the amount of space at the beginning of the operation. The Stack, which is built using a linked list, can hold any number of values for data as we desire.

Each new element in a linked list integration of a stack is added as a 'top' element, indicating that each newly integrated component is pointed by 'top.' When we want to remove an element of the Stack, we shift the node denoted by 'top' to its previous node within the list. The first element's following field must always be NULL.

2. Queues based on Linked Lists: A linked list arrangement can be used to implement the 'queue' data structure. The Queue, which is enforced by a linked list, may hold an endless amount of values. This indicates that a queue based on a linked list may handle data of variable size. There is no need to change the size at the beginning of the implementation. We may organize as many values of data as we like in the Queue using a linked list.

The node added last will always be denoted by rear during the linked list operation of a queue, while the node put first is always marked by 'front'.

3.Graph Implementation : Processes using a graph represented by the adjacency matrix are faster. However, if a graph is large, we cannot use such a large matrix to represent it; instead, we should use a grouping of adjacency lists that is tighter. Whenever a graph is sparse, using an adjacency list is the best solution. We're considering graph representation. Let's have a look at the simplest way to represent a graph using an array with adjacency lists. The main concept behind this technique is to keep a linked set of neighboring vertices for each vertex. We replace the only integer value head with another array (called heads) that contains the head of the list of all adjacent vertices for each vertex. Other arrays, such as data and next, remain the same for the remainder of the vertices. Another issue about using arrays instead of classes: we need to know which cells within arrays remain free and which are used. In our execution, we specify the value that is used, containing the total amount of used cells, and when we must obtain a free cell, we are going to use (used + 1). As a result, we have a way to implement an information structure for representing graphs.

4. Making Use of Hash Tables/ creating hashtable using linked list: Hash Tables implement a subset of dynamic set operations. In general, a set of keys is associated with a set of values depending on specified relationships. However, situations can arise in which multiple keys map to a precise location stipulated through the Hash function, resulting in a collision. Hash Table Chaining can help in this case. The chaining method avoids collisions by going ahead and placing all keys that correspond to a position in that slot while representing them in the form of a linked list. Chaining Hash Tables in Java is possible with both Doubly Linked Lists and Singly Linked Lists algorithms. Though the process of execution is identical, the only difference is that a Doubly Linked List allows for two-way traversal, which means that each node includes a reference to the next node as well as the previous node. As a result, the difficulty of deletion and addition at a known point is reduced to O(1) as opposed to O(n) for the Singly Linked List.

5. Handling large files using a linked list structure : A large file cannot be stored in a single location on a disc. As a result, there must be a way to link all of the scattered bits of the file. The use of linked lists enables an efficient file allocation technique in which each block of a file has a reference to the file's text block. The file chunks can be placed anywhere on the disc. This implies that, as with neighboring distribution, we may avoid fragmentation inside our disc.

This is a far more effective strategy that avoids wasting valuable space. Furthermore, linked list allocation places less strain on the directory because it only requires the file's beginning and ending pointers.

6. Using Linked Lists for Memory Management: Possessing a linked list of allocated memory segments and free memory sections, where a segment might be a process or a space between two processes, is another way to keep track of memory.Multiple algorithms can be used to allocate memory for a newly constructed process or a running process that is being read in from the disc when holes and operations are kept on a list that is organized by address. Here, we assume that the memory is aware of how much space it should set aside. Many different algorithms can be used to achieve this.

Below are the various categories of algorithms:

First fit: In this case, the memory manager examines the list of segments as well until it finds a hole that is large enough. The gap is divided into two sections: one for process and the other for unused memory. This algorithm is quick since it does as few searches as feasible.
Next fit : The only difference between this technique and the first-fit approach is that it maintains an account of each time it finds a good hole. It starts searching the list from exactly where it left off the last time when it is asked to find a hole.
Best fit: The best-fit algorithm searches the whole list and selects the smallest suitable hole. This technique seeks to find an opening that is near to the size that is necessary rather than dividing up a large hole that could be needed later.
Poor fit: This method always chooses the largest hole that is accessible, ensuring that the hole will be big enough when broken off to be helpful.
Quick fit: For a few of the most frequent sizes requested, this method maintains several lists.

Some other important applications of linked lists:

Operating systems: operating systems store lists of operations, memory allocations, file systems, and other information, and these operations are possible only because of a linked list.
Various audio/video streaming services: Streaming services for audio and video can employ linked lists to maintain track of playlists or suggested videos.
Browsers: Web browsers employ linked lists to operate the forward and backward buttons as well as to keep track of previously viewed websites.
Computer networks: A variety of communication and data structures protocols may be implemented in computer networks using linked lists.
Image processing: Linked lists are employed in applications for processing videos and images to convey pixels and frames.
Games: Linked lists may be employed to implement gaming logic, such as keeping track of an object's location in a game's universe or keeping a scoreboard for players.
Database Management Systems: Indexing patterns in systems for managing databases may be implemented using linked lists, enabling effective data search and retrieval.

So we have discussed basic introduction and various applications of linked lists. Still, before using them, we must be familiar with their advantages and disadvantages, so let's talk about a few significant advantages and disadvantages of linked lists.

Advantages of using linked list data structure :

1) Dynamic Collection Structure: Since linked lists are dynamic data structures that may be resized and expanded at runtimeruntime by memory deallocation and allocation, they don't require a starting size. An array, on the other hand, must have a defined beginning size and a maximum number of items which cannot be modified in any condition.

2) There is no memory loss : There is no wasted memory since a linked list's size may change as needed. Memory is only allocated as needed.In arrays, we must initialize them with a size that we can or cannot utilize completely, resulting in memory waste.

3) Basic implementation : A Linked List makes it simple to create certain extremely practical structures for data like queues and stacks.

4) Operation for Insertion and Deletion: As there is no requirement to move all elements after adding or eliminating them in a Linked List, these operations are quite simple. The only address that needs to be modified is the one in the pointers.

The following are some drawbacks of linked lists versus arrays:-

1) Memory usage: linked list contains both a data field and a pointer field in addition to its data field, it uses more memory than an array does. The location of the following node must also be stored in memory by the pointer field.

2) Random reach: In the case of a linked list, you must go through every node before node at position x in order to reach it. However, in the array, we'll use arr[x] to directly access the element at index x.

3) Traversing from the reverse : Reverse traversing is not feasible in a singly linked list since each node only holds the address of the node after it. Reverse traversal through a doubly-linked list is feasible, but it requires more memory since we need to set aside more space to keep the previous pointer. With the aid of a for loop, we can do a straightforward reverse traversal within arrays.

Conclusion

We covered a variety of linked list uses in this article. Every programming language, including C++, Python, Java, and C#, can implement lists, which are among the most popular and effective data structures. Linked lists are a flexible data structure with many practical uses in a variety of computer science domains. Linked lists are another useful tool for understanding how pointers work. It can be done to prepare yourself for more complex data structures like trees and graphs by practicing with linked lists.

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