Top 12 Data Structure Algorithms to Implement in Practical Applications in 2021
New Year…New Beginning…!!!
What’s your plan for this year??? (Being a programmer)
Of course, if you’re a programmer then this year you will also write the code, build the projects and you will solve a lot of coding questions.
Let’s talk about Data Structures and Algorithms…
Heart of computer science and the programmer’s breath to live in the coding world…
A lot of beginners start learning programming by picking up these two important tools of computer science. You might have practiced a lot but have you ever tried to know how these algorithms are helpful in the real-world application. Surely there are some reasons to learn them. Most of the newbie programmers learn it for the sake of a job but isn’t it interesting if we get to know the practical implementation of these algorithms in the real world.
The new year is coming and this new year we encourage you to check out the practical scenarios of famous algorithms instead of learning them just for the sake of a job. In this blog, we will discuss some practical implementations of these algorithms in the real world.
Surely you might have gone through implementing the program for the Fibonacci series once in your life. Being a student you might have asked to implement the program for the Fibonacci series or you might have asked this question during your interviews in XYZ companies.
Yes!!! We are talking about the same series where we apply the mathematical formula an = an−2+an−1 to get the series in our program. We implement the code to get the series 0, 1, 1, 2, 3, 5, 8, 13, and 21 on to infinity. In this series, we get the next highest number by adding the consecutive series.
You write the program, you clear your exams or you clear your interviews but have you ever tried to search that where this series is used in real-world application? What could be the possible scenario to utilize this algorithm in the real world?
The beauty of this sequence can be used to calculate miles to kilometers and vice versa. You will get a nearly accurate result (not accurate but accurate enough). In a Fibonacci sequence, you can consider any number as miles and the next number would be in kilometers.
Consider the sequence 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, …
In the above example, you can take two consecutive numbers 8 and 13. The smaller number is in miles i.e 8 and the bigger one is in kilometers i.e. 13.
8 in miles = 13 in kilometers.
This one is another popular algorithm among programmers. Palindrome number or string reads the same in reverse order. For example…level, madam, 12021. Implementing this algorithm is also a common question of the interview process in many companies.
You test your logical ability while implementing the program for palindrome numbers but can you just think about the practical scenario of this famous algorithm? Where it can be used?
Palindromes are used in DNA sequence processing. But how it is used in this processing?
A lot of DNA sequences are becoming available. To store the information about these DNA sequences we use molecular biology database. The capacity of these databases will be bigger in the future so it is important to communicate and store the data efficiently in the database.
It is important to compress these DNA sequences for better performance. To compress these sequences CTW (Context Tree Weighting Method) can be used. This method compresses the DNA sequences in less than two bits per symbol.
Mainly two characteristic structures of DNA sequences are known. One is palindrome or reverses compliments and the other one is approximate repeats. Using the hash and dynamic programming the algorithm searches the approximate repeat and palindrome before it encodes the next symbol. If it finds a palindrome or approximate repeat with enough length then the algorithm represents it with length and distance.
The first data structure to learn in programming…
Most commonly and most widely used data structure in many applications…
Every beginner’s programming journey starts with solving the questions of Array. Being a programmer you might have surely used this data structure a lot in your application. This data structure is used in every possible situation where you need to collect the object in one place. From simple to complex software or web application array is mostly used to store and display the data dynamically at web pages. Let’s take one of the good examples of using an array in a real-world application…
We all must have used the online ticket booking system at least once. It might be for booking tickets for train or maybe bus or flights or movies or any other shows. If we want to book any seat, then it’s just a matter of clicking on a square and it will be booked.
Have you ever wondered that the seat you book online on any system it’s a two-dimensional array?
When you’re booking a seat it lies somewhere in a specific row and column. This can be represented by a two-dimensional array such as a seat. So an array is applicable in all kinds of online booking systems. Hope you got the point and understood the real-world application of Array.
As a beginner, you might have surely read about the common example of stack data structure…a stack of plates or books in a cupboard but can you just think about another example of a stack apart from this basic one?
Is there any real-world application built and works on the concept of a Stack data structure?
Yes!!! There is…
A text editor such as notepad or Microsoft Word uses a stack data structure to accomplish undo tasks in their editor. Another good example of a stack is the browser’s working in your laptop or system.
Whenever you perform an activity in a text editor, a stack is created. Using the push operation you store the action, its metadata like the type of action, the nature of the action, its data, etc. Using the pop action you perform an undo operation and the last action (stored on the top of the stack) is removed or undone from the stack.
Another good example of a stack data structure is the Browser’s working on your laptop or system. Suppose you’re visiting www.google.com and then you visit www.geeksforgeeks.org. After that, you visit www.youtube.com. This information gets stored in the stack data structure using the push operation. When you click on the back button in your browser you go to the previous page which is the pop operation performed in the stack.
So if you’re on the page www.youtube.com and you’re pressing the back button then you visit the previous page www.geeksforgeeks.org. Pressing the back button again performs the pop operation and you get back to the page www.google.com.
5. Linked List
Another popular and common data structure among programmers is Linked List. Now think about the purpose of this data structure in a real-world application.
We all have a music player on our phones, and we have songs on it. Suppose you have 5-6 songs on your list. When you create a playlist for these songs it works on the concept of the linked list. One by one these songs are played and this is one of the best examples of the singly linked list. Songs are connected and you can go from song three to song four but you can not go back (behavior of singly linked list).
When you implement the functionality to play the song in both directions, it follows the behavior of a doubly linked list. In a doubly-linked list, nodes are connected in both directions. So in a playlist, you can move from song 3 to song 4 as well as song 3 to song 2. You will have both previous and next buttons. So bidirectional navigation is possible.
When you play the songs in repeat mode it follows the behavior of a circular linked list. In a circular linked list, the last node is connected with the first node. So once the last song is completed the first song will play again and it will play in the cyclic mode and it will never stop.
Being a programmer you might be aware of the binary search algorithm. This algorithm is also known as half interval search, logarithmic search, or binary chop. In this algorithm, we search for the target value within a sorted array.
This algorithm makes the searching process easier because you don’t need to compare each element in the list of numbers. Binary search is the fast way to search the target value in the ordered list of data. It gives you the power to do this process efficiently. You can find a lot of examples of binary search algorithms such as searching the meaning of the word in a dictionary, but do you know anyone of a real-world application that uses the binary search method?
One of the real-world scenarios of this algorithm is validating user credentials in an application. Using the binary search you can validate the millions of user’s credentials within a fraction of seconds.
This algorithm also used in many programming languages libraries such as Java, .NET, C++ STL, and so on. Python’s list.sort() method uses Timsort which (AFAIK) uses binary search to locate the positions of elements. Binary search is also used in 99% of 3D games and applications.
Merge sort works on the concept of divide and conquer technique. We divide the list into several sublist until the sublist doesn’t contain a single element. After that, we merge these sublists to get the sorted list of elements. This is a simple and short introduction to this algorithm but do you know where it is used in real-world applications.
A lot of people love to do online shopping through any e-commerce website. Do you know that these e-commerce websites use this algorithm? Most of the e-commerce sites have the section “You might like”. This section maintains the array of all the user accounts and then whichever has the least number of inversion with your array of choices, start recommending what they have bought, or they like. (Next time this section will remind you of the uses of binary search while doing shopping on these websites)
Another popular program among programmers is checking the number if it is Armstrong or not. In Armstrong numbers, the sum of cubes of digits of a number is equal to the number itself. For example, 153 and 371 is an Armstrong number. Armstrong numbers are mostly used in data security applications for data encryption and decryption.
Visit the link of IJITEE. Armstrong number for wireless sensor networks are mentioned. They have used Armstrong based security algorithms where a 128-bit key is generated using the Armstrong number. It is used in the AES algorithm for data encryption and decryption.
Huffman coding is used in conjunction with cryptography and data compression. It is used for lossless data compression. Based on the probability, it is implemented in a way that you do not need to keep multiple copies of the same thing.
Huffman coding is used in compression formats such as GZIP, PKZIP (winzip, etc), and BZIP2. All the communication with and from the internet uses the Huffman encoding. Most of the image files such as JPEG and PNG are Huffman encoded. Also, music files such as MP3s are Huffman encoded.
Huffman code converts the fixed-length codes into variable-length codes. This is further compressed using JPEG and MPEG techniques that generate the desired compression ratio.
Another favorite topic for computer science students and for programmers is dynamic programming. 0-1 Knapsack Problem, Wordbreak problems, Longest Common Subsequence all these problems are the most popular and common problems of dynamic programming. You solve it, you use your logical ability but where actually in the real world this concept is used…
Dynamic programming is widely used in bioinformatics, mathematics, and economics. In bioinformatics tasks such as sequence alignment, protein folding, RNA structure prediction, and protein-DNA binding uses dynamic programming.
In mathematics, DP is used in matrix multiplication which is widely used in Rocket technology. The path of the rockets is decided by solving many parameters. All the decision-making problems can be solved optimally using dynamic programming.
Whether you’re traveling somewhere, going outside or you’re trying to find the route to your specific destination. You use your best friend in your phone Google Map. Do you know that Google Map uses the Graph data structure?
The graph data structure is a very powerful data structure. Not only the earth but the whole universe can be represented by the graph. From tiny subatomic particles to the gigantic universe, you can represent each and everything with the help of Graph.
When you’re using a Google map, all the cities and states are connected like a graph with distance information. There are many ways to reach from one city to the other one but to find the shortest path between the two cities you need to use some algorithms. Dijkstra’s algorithms which is a very powerful algorithm can be implemented to find the shortest path between the two cities.
To decide the shortest path to your destination, Dijkstra’s algorithm enables your navigation system/GPS in your phone. Uber uses Hungarian Algorithm to assign each car to people looking for a ride.
Facebook also uses the graph data structure to implement the news feed or followers. It uses Graph API to implement most of the things in their application. Everything can be represented by the vertices or node such as Pages, Places, Groups, Comments, Photos, Photo Albums, Stories, Videos, Notes, etc. Every connection or relationship is an edge on Facebook. Graph API stores the data in the form of vertices and edges.
This one is an advanced data structure topic for programmers. You learn it may be for the sake of the job, you also enjoy solving questions based on it but what’s the use of this advanced topic in the real-world application. Where is it implemented in our day-to-day life? Let’s come to that interesting answer…
You use your mobile phone every day, you also use the swipe features in it. This swipe features in your mobile keypad and the auto-correct while writing a document uses a Trie data structure. Trie data structure holds the character values in your phone.
Network browser history also uses a Trie data structure. The URLs of the site, you have visited are organized by the Trie data structure. When a user types the prefix of the previously used URL, browser’s complete the URL using this powerful Data Structure.
Now you’re aware of the practical use cases of the famous data structures and algorithms. Isn’t it interesting to know that how these famous algorithms are implemented in our day-to-day life?
Many of us had no knowledge about the interesting use cases of these data structures and algorithms. We were using it somewhere, but we weren’t aware of it. It’s always good to know the benefits of something before you pick up to learn anything. These were just a bunch of data structures and algorithms we have introduced but there are several algorithms we use in our day-to-day life.
Now, this new year thinks about the practical use cases of the other algorithms…
Also, this new year not just learn these algorithms for the sake of learning them, but also learn these algorithms to implement some interesting real-world application on your own.