Independently published, 2021. — 186 p. — ISBN: 9798591756123.
Data Structures are the programmatic way of storing data so that data can be used efficiently. Almost every enterprise application uses various types of data structures in one or the other way. This tutorial will give you a great understanding on Data Structures needed to understand the complexity of enterprise level applications and need of algorithms, and data structures.
Why to Learn Data Structure and Algorithms?As applications are getting complex and data rich, there are three common problems that applications face now-a-days.
Data Search − Consider an inventory of 1 million(106) items of a store. If the application is to search an item, it has to search an item in 1 million(106) items every time slowing down the search. As data grows, search will become slower.
Processor speed − Processor speed although being very high, falls limited if the data grows to billion records.
Multiple requests − As thousands of users can search data simultaneously on a web server, even the fast server fails while searching the data.
To solve the above-mentioned problems, data structures come to rescue. Data can be organized in a data structure in such a way that all items may not be required to be searched, and the required data can be searched almost instantly.
Applications of Data Structure and AlgorithmsAlgorithm is a step-by-step procedure, which defines a set of instructions to be executed in a certain order to get the desired output. Algorithms are generally created independent of underlying languages, i.e. an algorithm can be implemented in more than one programming language.
From the data structure point of view, following are some important categories of algorithmsSearch − Algorithm to search an item in a data structure.
Sort − Algorithm to sort items in a certain order.
Insert − Algorithm to insert item in a data structure.
Update − Algorithm to update an existing item in a data structure.
Delete − Algorithm to delete an existing item from a data structure.
The following computer problems can be solved using Data StructuresFibonacci number series
Knapsack problem
Tower of Hanoi
All pair shortest path by Floyd-Warshall
Shortest path by Dijkstra
Project scheduling
AudienceThis book is designed for Computer Science graduates as well as Software Professionals who are willing to learn data structures and algorithm programming in simple and easy steps.
Data Sttuctures & AlgorithmsDSA Introduction
DSA Overview
DSA Environment Setup
AlgorithmDSA – Algorithms Basic
DSA – Asymptotic Analysis
DSA – Greedy Algorithms
DSA – Divide and Conquer
DSA – Dynamic Programming
Data StructureDSA – Data Structure Basics
DSA – Array Data Structure
Linked ListDSA – Linked List Basics
DSA – Doubly Linked List
DSA – Circular Linked List
Stack & QueueDSA- Stack
DSA – Expression Parsing
DSA – Queue 3
Searching TechniquesDSA – Linear Search
DSA – Binary Search
DSA – Interpolation Search
DSA – Harsh Table
Sorting TechniqueDSA – Sorting Algorithms
DSA – Bubble Sort
DSA – Insertion Sort
DSA – Selection Sort
DSA - Merge Sort
DSA – Shell Sort
DSA – Quick Sort
Graph Data StructureDSA – Graphic Data Structure
DSA – Depth First Traversal
DSA – Breadth First Traversal
Tree Data StructureDSA – Tree Data Structure
DSA – Tree Traversal
DSA – Binary Search Tree
DSA – AVL Tree 4
DSA – Spanning Tree
DSA – Heap
RecursionDSA – Recursion Basics
DSA – Tower of Hanoi
DSA – Fibonacci Series