Data-Structure-And-Algorithm

Data Structure & Algorithm with C Programming Language

What is Data Structure ?

To simply put, data structure is an orderly arrangement of data in computers to use it in a more efficient manner. It is a collection of data objects that allows storing, organizing, and retrieving data on systems.

A majority of data structures are inspired from real life scenarios. For instance, have you been scolded by your parents for not being able to find a particular outfit in your messy wardrobe? Yes, right? Your parents give the advice to keep your clothes in a systematic manner so the next time you want something you can easily pick it up. In this situation, you need to arrange & keep your clothes (data) in such a structure that when searching for a particular thing you don’t have to hassle much.

We are using data structures in our everyday lives without even knowing it. From our contact list, book piles to organizing hierarchy or to-do list, we are applying different arrangement techniques which are called as data structures in the computing realm. Data structure provides the right way to organize information in the digital space.

The data structure is a key component of Computer Science and is largely used in the areas of Artificial Intelligence, operating systems, graphics, etc.

Data structures store objects and allow their manipulation on the basis of two different types:

What is an Algorithm ?

Algorithm refers to a set of steps used in completing a certain task or to get a desired output. It is like building blocks for programming that allows smartphones, computers or websites to function smoothly and make decisions. Each code written by a programmer is a collective formation of algorithms navigating what to do. Algorithms are well-defined procedures that help computers to solve problems.

Let’s take a simple example of GPS. When you search a location, GPS uses an algorithm to search for multiple available routes, also for checking the current traffic GPS uses a different algorithm, based on the collective information it provides the best available route for you. All these algorithms are in-built   into the GPS’ code. So, if there is any error in the code of GPS, it won’t function correctly, thus provide incorrect direction. Computers use algorithms to calculate things much faster than the humans.

What is relationship between Data Structures and Algorithm ?

Both Data structures and algorithms are interrelated and complement each other. An algorithm applies to a particular data structure, while using the right data structure helps to drastically improve the performance of an algorithm. Hence, we can’t detach data structures and algorithms.

Following are the main categories of algorithms in relation to data structures:

• Insert – To insert an item in a data structure, this algorithm is applicable.
• Update – The update algorithm is useful for updating an existing item in a data structure.
• Delete – In order to delete an existing item from a data structure, you can use the delete algorithm.
• Search – This algorithm helps in finding an item in a data structure.
• Sort – This algorithm is helps to sort items in a specific order.

Why importance to learn Data Structures and Algorithms ?

Data structures and algorithms are the most pivotal topics for programmers and Computer Science graduates, to get a job & perform well in it. Here are some considerable reasons to learn data structures and algorithms:

• A comprehensive knowledge of data structures in combination with algorithms is the core foundation of writing good codes. It reduces coding costs & enhances data accuracy, which is the ultimate goal of organizations.
• To earn salaries as high as the developers of Amazon and Google, you need to improve your problem-solving abilities by mastering data structures and algorithms.
• If you want to generate bug-free results in coding, then it is utmost important to excel these concepts.
• Learning data structures and algorithms is also beneficial for a better understanding of new frameworks such as Angular, React, Vue, Spring MVC, etc.
• When you get an exposure to a different range of problem-solving techniques, it helps you take up the next challenging problem easily.
• Programmers who are competent in data structures and algorithms can easily perform the tasks related to data processing, automated reasoning, or calculations. 
• Data structure and algorithm is significant for developers as it shows their problem-solving abilities amongst the prospective employers. Thus, amplifies the chances of getting the job.

What are topics to Data Structures and Algorithm learn for Competitive Programming ?

Data structure and algorithm is a vast subject altogether, however there are some key topics you must prepare before going for an interview:

• Role of Algorithms and Data Structures in problem solving
• Types of Data Structures
• Identifying techniques for designing Algorithms
• Sorting Data by using Bubble Sort Algorithm
• Performing Linear Search
• Sorting Data by using Selection Sort Algorithm
• Implementing Binary Search
• Sorting Data by implementing Shell Sort Algorithm
• Dynamic Memory Allocation
• Inserting a Node in a Linked List
• Traversing a Doubly-Linked List
• Implementing a Circular Linked List
• Sorting Data by implementing Merge Sort Algorithm
• Adding Polynomials Using Linked Lists
• Implementing a Stack using an Array
• Implementing a Stack using a Linked List
• Identifying various operations on Queues
• Implementing a Queue using an Array
• Hashing
• Storing Data in a Tree
• Implementing a Binary Search Tree
• Indexing & defining a Threaded Binary Tree
• Height Balanced Tree
• Graph Storing Data in a Graph

Repository Content Of Glance

• Array
  • Type Of Array
    • 1D Array
    • 2D Array
  • Array Operation
    • Traversal
    • Insertion
    • Deletion
    • Searching
    • Sorting
    • Calculate of Length
    • Reverse a Array
  • Pointer in Array
• LinkedList
  • Single LinkedList
  • Doubly LinkedList
  • Circular LinkedList
  • Doubly Circular LinkedList
• Stack
• Queue
• Tree
• Graph
• Searching Algorithm
  • Linear Search
  • Binary Search
  • Jump Search
  • Interpolation Search
  • Exponential Search
  • Sublist Search (Search a linked list in another list)
  • Fibonacci Search
  • The Ubiquitous Binary Search
  • Recursive program to linearly search an element in a given array
  • Recursive function to do substring search
  • Unbounded Binary Search Example (Find the point where a monotonically increasing function becomes positive first time)
• Sorting Algorithm
  • Selection Sort
  • Bubble Sort
  • Recursive Bubble Sort
  • Insertion Sort
  • Recursive Insertion Sort
  • Merge Sort
  • Iterative Merge Sort
  • Quick Sort
  • Iterative Quick Sort
  • Heap Sort
  • Counting Sort
  • Radix Sort
  • Bucket Sort
  • ShellSort
  • TimSort
  • Comb Sort
  • Pigeonhole Sort
  • Cycle Sort
  • Cocktail Sort
  • Strand Sort
  • Bitonic Sort
  • Pancake sorting
  • Binary Insertion Sort
  • BogoSort or Permutation Sort
  • Gnome Sort
  • Sleep Sort – The King of Laziness / Sorting while Sleeping
  • Structure Sorting (By Multiple Rules) in C++
  • Stooge Sort
  • Tag Sort (To get both sorted and original)
  • Tree Sort
  • Cartesian Tree Sorting
  • Odd-Even Sort / Brick Sort
  • QuickSort on Singly Linked List
  • QuickSort on Doubly Linked List
  • 3-Way QuickSort (Dutch National Flag)
  • Merge Sort for Linked Lists
  • Merge Sort for Doubly Linked List
  • 3-way Merge Sort
• Special Algorithm
  • Analysis of Algorithms
  • Greedy Algorithms
  • Pattern Searching
  • String Algorithms
  • Backtracking
  • Divide and Conquer
  • Geometric Algorithms
  • Mathematical Algorithms
  • Bit Algorithms
  • Graph Algorithms
  • Randomized Algorithms
  • Branch and Bound
  • Quizzes on Algorithms
• Dynamic Programming

Conclusion Of Data Structure & Algorithm

The technology will only be going to become better at what it does as long as programming & coding continues to flourish. Therefore, the importance of data structures and algorithms will remain persistence for the functioning of technologies, navigating what they do & how they do it.

HAPPY PROGRAMMING 😀 & I LOVE PROGRAMMING 💖

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