BFS Algorithm | Breadth First Search Algorithm Tutorial | Data Structures And Algorithm |Simplilearn

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This video is based on Breadth-First Search or BFS in Data Structures. This Simplilearn's Data Structures and Algorithms Tutorial will help beginners to understand what is Breadth-first search with an example in data structures and algorithms. This video on BFS Algorithm with a practical demo for a better learning experience. This tutorial includes the following topics.

00:00 Introduction to BFS Algorithm
00:50 What is BFS Algorithm (Breadth First Search Algorithm)?
01:00 Example of BFS Algorithm (Breadth First Search Algorithm)

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The breadth-first search or BFS algorithm is used to search a tree or graph data structure for a node that meets a set of criteria. It begins at the root of the tree or graph and investigates all nodes at the current depth level before moving on to nodes at the next depth level. You can solve many problems in graph theory via the breadth-first search. For example, finding the shortest path between two vertices a and b is determined by the number of edges. In a flow network, the Ford–Fulkerson method is used to calculate the maximum flow and when a binary tree is serialized/deserialized instead of serialized in sorted order, the tree can be reconstructed quickly.

What Is a Data Structure?
The short answer is: a data structure is a specific means of organizing data in a system to access and use. The long answer is a data structure is a blend of data organization, management, retrieval, and storage, brought together into one format that allows efficient access and modification. It’s collecting data values, the relationships they share, and the applicable functions or operations.

Why Is Data Structure Important?
The digital world processes an increasing amount of data every year. According to Forbes, there are 2.5 quintillion bytes of data generated daily. The world created over 90 percent of the existing data in 2018 in the previous two years! The Internet of Things (IoT) is responsible for a significant part of this data explosion. Data structures are necessary to manage the massive amounts of generated data and a critical factor in boosting algorithm efficiency. Finally, since nearly all software applications use data structures and algorithms, your education path needs to include learning data structure and algorithms if you want a career as a data scientist or programmer. Interviewers want qualified candidates who understand how to use data structures and algorithms, so the more you know about the concepts, the more comfortably and confidently you will answer data structure interview questions.