More than 70% of companies use Data Structures and Algorithms to filter candidates.
It is extremely crucial to learn Data Structures and Algorithms for cracking a job interview in a product-based company.
For the upcoming few minutes, we’ll learn about the need for data structures using Java programming language and why they are so important to get a job.
Thereafter, we’ll look at different types of data structures with real-life examples (yes, you will connect a lot!) and their syntax and algorithms in Java.
Let’s deep dive in!
Why do we need to learn Data Structures in Java?
Imagine 3 different Scenarios
- If we give you a thick dictionary to find the meaning of the word “Aggrandize” but the dictionary is unsorted.
- If we give you a map to find a route for a famous restaurant, but the map is in tabular format with a location in its latitude and longitudinal measure.
- If we ask you to share your Birthday pictures, but your Gallery saves data randomly and not date-wise.
In these situations, you have all the data that’s required, but the structure is absolutely inefficient and unorganized.
Thus, to utilize data most efficiently it needs to be structured in a way that maximizes its readability.
- A sorted Dictionary
- A plotted Map
- A linear stack of Photos
Computers work with a wide variety of data, including texts, images, videos, geospatial information, and much more. So even with brilliant computational power, the right kind of logical structure is a must for saving time and space for a Java application.
What is Java?
Java language is one of the most popular programming languages developed by Sun Microsystem in 1995. It is a platform-independent language and thus can run on billions of devices. It is an easy-to-understand language and proves to be an efficient mode for learning the implementation of Data Structures.
Data Structures in java are given high importance in interviews and coding rounds because it is the most basic concept in computer science and having a good understanding is important to develop software in java with excellent performance and functionality.
What are Data Structures in Java?
Data Structure is an arrangement of data in a computer’s memory. It includes Arrays, Stacks, Queues, Linked lists, binary trees, hash tables, etc.
We use algorithms to manipulate the data in these structures in various ways, broadly inserting new data elements, deleting, searching, and sorting.
Let’s look at some significant structures used to store data.
Types of Data Structures in Java
Data structures are broad of two types,
- Linear data Structure – when they are stored linearly, as in Arrays, Linked List.
- Non-linear Structure – when data is structured in a non-linear way, as in Trees, Graphs.
Let’s discuss each of them one by one.
Linear Data Structure
Arrays
In the recent past, there used to be a stack of Indexed cards that had information like the name, age, etc. of citizens. So when a new citizen was added, they were given a new indexed card. When there was the need to search, the index number was looked at and the card was drawn out.
This is no longer used thanks to computers using the same concept named “Arrays”.
“Array is the collection of similar data elements stored in contiguous memory locations. Each element’s unique index can be accessed using the index.”
Arrays are used so widely that they are predefined in almost all languages.
Here’s an example of an Array in JAVA and some mostly-used operations,
When to use Arrays
- The size of the data is known
- Dealing with similar data types
- When you need to search from between.
Next, we learn about stacks and queues.
More than being data structures they are created and used to carry out tasks and once completed, they are discarded.
Stacks
Remember the toy having Rings of increasing size on a rod? The ring from the middle could not be taken out. Only the top ring could be removed one at a time.
That’s the structure of a Stack.
A Stack is a linear data structure that follows the principle of LIFO (Last In First Out) and allows the insertion and deletion only from the top.
The operation of inserting the (new) top element is called Push.
The operation of deleting the top element is called Pop.
Java program to implement Stack Operations :
Queue
Queue works exactly like the waiting lines at ticket counters (but way more disciplined). The person first entering the queue gets the ticket first.
The queue is a linear data structure that follows the principle of FIFO (First In First Out) and allows insertion from one side and deletion from the other.
Java program to implement queue :
Linked list
Arrays are useful when we have continuous memory cells. But say we need to create a list of 5 elements, but there are 3 empty cells at one place and 2 empty cells at another. So the solution is to link them together.
Let me give an example
Suppose a school plans a movie day for its students. When Booking the tickets, they found seats in one row itself. So the teacher notes the row and the first and the last seat number.
But suppose, the seats were available at different places. Now to remember where the students are seated, what the teacher does is, takes a paper and note down the seat number of Student 1. She then tells Student 1 to note and keep the seat number of Student 2. Student 2 to keep seat number of Student 3 and so on. Thus creating a Link among students.
So after the show, when the teacher comes to collect them, she can go to Student 1, and then to Student 2, and so on.
This my friend, is a Linked List.
A linked list is a connection of Nodes, where each node has two parts, one for storing the data and two for storing the link to the next node.
Non-Linear Data Structures
Trees
Trees are widely used due to their efficiency in organizing and searching data.
Say for example, in a University database, I need to look for data of a Student. If the data is arranged in hierarchical form,
Trees are widely used due to their efficiency in organizing and searching data.
then I can quickly look at a branch, and find it easily without scanning other branches as in Array. This makes searching more efficient.
The tree data structure has a root node, branches, and sub-branches. The last nodes are called Leaves.
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Graphs
A graph is just like a Tree, a collection of objects (nodes/ vertices), connected through a set of Edges.
Unlike trees, we have a set of vertices connected through edges connected in any way possible. There’s no defined structure or hierarchy.
Major applications can be found in Google maps, Social networks, the world wide web, Blockchain, etc.
Conclusion-
The concept of Data Structure goes deep and wide. And so, connecting it with things we know and visualize is the key to mastering Data Structures.
At Tap Academy, using Augmented Reality and interactive sessions, we help you understand the concepts easily and deeply to prepare you to crack the coding interviews.
If you want to see how this works, join the free workshop and get one step close to Mastering DSA.
