Data Structures Tutorial

Data Structures Tutorial Asymptotic Notation Structure and Union Array Data Structure Linked list Data Structure Type of Linked list Advantages and Disadvantages of linked list Queue Data Structure Implementation of Queue Stack Data Structure Implementation of Stack Sorting Insertion sort Quick sort Selection sort Heap sort Merge sort Bucket sort Count sort Radix sort Shell sort Tree Traversal of the binary tree Binary search tree Graph Spanning tree Linear Search Binary Search Hashing Collision Resolution Techniques

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Priority Queue in Data Structure Deque in Data Structure Difference Between Linear And Non Linear Data Structures Queue Operations In Data Structure About Data Structures Data Structures Algorithms Types of Data Structures Big O Notations Introduction to Arrays Introduction to 1D-Arrays Operations on 1D-Arrays Introduction to 2D-Arrays Operations on 2D-Arrays Strings in Data Structures String Operations Application of 2D array Bubble Sort Insertion Sort Sorting Algorithms What is DFS Algorithm What Is Graph Data Structure What is the difference between Tree and Graph What is the difference between DFS and BFS Bucket Sort Dijkstra’s vs Bellman-Ford Algorithm Linear Queue Data Structure in C Stack Using Array Stack Using Linked List Recursion in Fibonacci Stack vs Array What is Skewed Binary Tree Primitive Data Structure in C Dynamic memory allocation of structure in C Application of Stack in Data Structures Binary Tree in Data Structures Heap Data Structure Recursion - Factorial and Fibonacci What is B tree what is B+ tree Huffman tree in Data Structures Insertion Sort vs Bubble Sort Adding one to the number represented an array of digits Bitwise Operators and their Important Tricks Blowfish algorithm Bubble Sort vs Selection Sort Hashing and its Applications Heap Sort vs Merge Sort Insertion Sort vs Selection Sort Merge Conflicts and ways to handle them Difference between Stack and Queue AVL tree in data structure c++ Bubble sort algorithm using Javascript Buffer overflow attack with examples Find out the area between two concentric circles Lowest common ancestor in a binary search tree Number of visible boxes putting one inside another Program to calculate the area of the circumcircle of an equilateral triangle Red-black Tree in Data Structures Strictly binary tree in Data Structures 2-3 Trees and Basic Operations on them Asynchronous advantage actor-critic (A3C) Algorithm Bubble Sort vs Heap Sort Digital Search Tree in Data Structures Minimum Spanning Tree Permutation Sort or Bogo Sort Quick Sort vs Merge Sort Boruvkas algorithm Bubble Sort vs Quick Sort Common Operations on various Data Structures Detect and Remove Loop in a Linked List How to Start Learning DSA Print kth least significant bit number Why is Binary Heap Preferred over BST for Priority Queue Bin Packing Problem Binary Tree Inorder Traversal Burning binary tree Equal Sum What is a Threaded Binary Tree? What is a full Binary Tree? Bubble Sort vs Merge Sort B+ Tree Program in Q language Deletion Operation from A B Tree Deletion Operation of the binary search tree in C++ language Does Overloading Work with Inheritance Balanced Binary Tree Binary tree deletion Binary tree insertion Cocktail Sort Comb Sort FIFO approach Operations of B Tree in C++ Language Recaman’s Sequence Tim Sort Understanding Data Processing Applications of trees in data structures Binary Tree Implementation Using Arrays Convert a Binary Tree into a Binary Search Tree Create a binary search tree Horizontal and Vertical Scaling Invert binary tree LCA of binary tree Linked List Representation of Binary Tree Optimal binary search tree in DSA Serialize and Deserialize a Binary Tree Tree terminology in Data structures Vertical Order Traversal of Binary Tree What is a Height-Balanced Tree in Data Structure Convert binary tree to a doubly linked list Fundamental of Algorithms Introduction and Implementation of Bloom Filter Optimal binary search tree using dynamic programming Right side view of binary tree Symmetric binary tree Trim a binary search tree What is a Sparse Matrix in Data Structure What is a Tree in Terms of a Graph What is the Use of Segment Trees in Data Structure What Should We Learn First Trees or Graphs in Data Structures All About Minimum Cost Spanning Trees in Data Structure Convert Binary Tree into a Threaded Binary Tree Difference between Structured and Object-Oriented Analysis FLEX (Fast Lexical Analyzer Generator) Object-Oriented Analysis and Design Sum of Nodes in a Binary Tree What are the types of Trees in Data Structure What is a 2-3 Tree in Data Structure What is a Spanning Tree in Data Structure What is an AVL Tree in Data Structure Given a Binary Tree, Check if it's balanced B Tree in Data Structure Convert Sorted List to Binary Search Tree Flattening a Linked List Given a Perfect Binary Tree, Reverse Alternate Levels Left View of Binary Tree What are Forest Trees in Data Structure Compare Balanced Binary Tree and Complete Binary Tree Diameter of a Binary Tree Given a Binary Tree Check the Zig Zag Traversal Given a Binary Tree Print the Shortest Path Given a Binary Tree Return All Root To Leaf Paths Given a Binary Tree Swap Nodes at K Height Given a Binary Tree Find Its Minimum Depth Given a Binary Tree Print the Pre Order Traversal in Recursive Given a Generate all Structurally Unique Binary Search Trees Perfect Binary Tree Threaded Binary Trees Function to Create a Copy of Binary Search Tree Function to Delete a Leaf Node from a Binary Tree Function to Insert a Node in a Binary Search Tree Given Two Binary Trees, Check if it is Symmetric A Full Binary Tree with n Nodes Applications of Different Linked Lists in Data Structure B+ Tree in Data Structure Construction of B tree in Data Structure Difference between B-tree and Binary Tree Finding Rank in a Binary Search Tree Finding the Maximum Element in a Binary Tree Finding the Minimum and Maximum Value of a Binary Tree Finding the Sum of All Paths in a Binary Tree Time Complexity of Selection Sort in Data Structure How to get Better in Data Structures and Algorithms
Data Structures Algorithms
2022-04-24 15:28:34

Data Structures Algorithms

What is an Algorithm?

An algorithm is a sequence of steps used to complete a job or get a desired result. It is similar to programming building elements that let cell phones, computers, or websites to run smoothly and make judgments. Each line of code generated by a programmer is a collection of algorithms that determine what to perform. Algorithms are well-defined techniques that assist computers in problem solving.

Let's look at GPS as an example. When you search for a destination, GPS utilises an algorithm to search for many accessible routes. GPS also uses a different algorithm to check current traffic, and based on the collective information, it delivers the best possible route for you. All of these techniques are included into the GPS software. As a result, if there is a mistake in the GPS code, it will not operate properly, offering inaccurate directions. Algorithms are used by computers to perform calculations considerably faster than humans.

Data Structures Algorithms

How is Data Structure and Algorithm related?

Data structures and algorithms are inextricably linked and mutually beneficial. An algorithm applies to a certain data structure, and employing the correct data structure significantly improves an algorithm's performance. As a result, we can't separate data structures and algorithms.

The primary types of algorithms in respect to data structures are as follows:

  • Search– This method aids in the discovery of an object within a data structure.
  • Insert– This algorithm may be used to insert an item into a data structure.
  • Sort– This algorithm aids in the arrangement of objects in a given order.
  • Update– The update method may be used to update an existing item in a data structure.
  • Delete– The delete algorithm may be used to remove an existing item from a data structure.
Data Structures Algorithms

Why learn Data Structure and Algorithm?

Data structures and algorithms are the most important topics for programmers and Computer Science graduates to understand in order to acquire a job and do well in it. Here are a few compelling reasons to study data structures and algorithms:

  • The essential basis of producing good code is a thorough understanding of data structures in conjunction with algorithms. It lowers coding costs while improving data accuracy, which is the ultimate aim of enterprises.
  • To earn salary comparable to those of Amazon and Google developers, you must increase your problem-solving skills by learning data structures and algorithms.
  • It is critical to master these ideas if you wish to produce bug-free output when coding.
  • Learning data structures and algorithms may also help you comprehend new frameworks like Angular, React, Vue, Spring MVC, and others.
  • When you are exposed to a variety of problem-solving strategies, it makes it easier to tackle the next difficult challenge.
  • Data structure and algorithm experts can readily accomplish jobs involving data processing, automated reasoning, or computations.
  • Data structure and algorithm are important for developers since they demonstrate their problem-solving talents to prospective employers. As a result, the chances of receiving the job are increased.

The choice of data structure method can be the difference between a programme running in a few seconds and a programme running for several days. You can only make an excellent decision if you have that degree of advanced knowledge of data structures and algorithms.

Algorithms and data structures Learning Topics for Competitive Programming

Although data structure and algorithm are large subjects in their own right, there are a few crucial areas you should be familiar with before attending an interview:

  • Algorithms and Data Structures' Role in Problem Solving
  • Data Structure Varieties
  • Identifying Algorithm Design Techniques
  • Using the Bubble Sort Algorithm to Sort Data
  • Linear Search is being performed.
  • Using the Selection Sort Algorithm to Sort Data
  • Binary Search is being implemented.
  • Sorting data using the Shell Sort Algorithm.
  • Allocation of Dynamic Memory
  • Adding a Node to a Linked List.
  • navigating a doubly-linked list
  • Putting a Circular Linked List in Place.
  • Sorting data using the Merge Sort Algorithm.
  • Using Linked Lists to Add Polynomials
  • Using an Array to implement a Stack.
  • Using a Linked List to implement a Stack.
  • Identifying various Queue procedures.
  • Using an Array to implement a Queue.
  • Hashing
  • Data Storage in a Tree
  • Creating a Binary Search Tree.
  • Creating and indexing a Threaded Binary Tree.
  • Tree with a balanced height.
  • Graph Data Storage in a Graph

Conclusion

As long as programming and coding are alive and well, technology will only get better at what it does. As a result, the relevance of data structures and algorithms in the working of technologies, navigating what they do and how they do it, will stay constant.