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A complete guide to graph search algorithms for interview preparation! We explore DFS (depth-first search) and BFS (breadth-first search) with code examples in Python, Java, JavaScript, C++, and Go. We focus on the 2D grid, which is the most common grid used in interviews. 🎯 WHAT YOU'LL LEARN: When to use DFS and when to use BFS How to find a path between points Finding the shortest route Counting connected components Stack overflow problems and their solutions Estimating complexity in Big O How to present a solution in an interview 💻 CODE IN 5 LANGUAGES: Python Java JavaScript C++ Go ⏱️ TIMESTAMPS: 00:00 - Hi 00:21 - Why graph algorithms are needed 00:38 - About maps 00:46 - What maps consider when plotting a route 00:56 - Checking a path on a grid of cells 01:44 - Think like a computer... 02:10 - Depth-first search (DFS) algorithm 02:22 - Depth-first search (DFS) animation 02:58 - Graph traversal logic in DFS 03:45 - Returning to the pathfinding animation from A to B 04:37 - What if we shorten the path? 05:19 - What if there is no path? How does DFS work then? 05:32 - What's the plan next? 05:55 - The Secret to Understanding Graphs 06:04 - Storing a Graph as a Map in Memory 06:25 - Code for Checking a Path from A to B Using Depth-First Search (Python) 07:30 - The Magic of Depth-First Search 07:45 - The Structure of Writing Depth-First Search (DFS) 08:07 - Understanding It All at Once Isn't Easy... 08:26 - Java, JavaScript, C++, Go: Depth-First Search 08:40 - Problem: Coloring by Numbers 09:30 - Learning to Color Adjacent Cells with Depth-First Search 10:36 - Code for Filling Neighbors 11:05 - Java, JavaScript, C++, Go: Filling Neighbors 11:12 - Learning to Count Fills 12:21 - Code for Counting Fills (Python) 12:57 - Java, JavaScript, C++, Go: Counting Components Connectedness 13:10 - The Problem of Large Matrices... 13:33 - Main Memory Areas 13:44 - Limitations of Stack Memory 14:12 - Solving Stack Overflow 14:37 - Code for an Iterative Implementation of Connected Component Counting (Python) 15:02 - About Using the Stack 15:13 - Back to the Code 15:58 - Java, JavaScript, C++, Go: Iterative Counting of Connected Components 16:09 - Important Disclaimer 16:19 - Estimating Time and Memory in Big O 17:21 - Worst-Case Memory Estimation 17:25 - Typical Estimation for Depth-First Search (DFS) 17:32 - Time and Memory for Checking a Path from A to B 17:50 - What is Expected of You in an Interview 17:57 - Recursive vs. Iterative Depth-First Search 18:18 - You Handsome! 18:30 - About the practice 19:20 - Shortest path algorithms 19:31 - The problem of finding the minimum distance from A to B 19:58 - Animation of breadth-first search (BFS) 20:22 - The basis for writing breadth-first search... 20:44 - How to replace the queue in breadth-first search (BFS) 21:11 - An idea for finding the shortest distance from A to B 23:15 - Breadth-first search code (Python) 24:12 - Java, JavaScript, C++, Go: breadth-first search 24:22 - A closer look at traversing cell neighbors 24:42 - A typical mistake when implementing breadth-first search 25:09 - Interesting fact about breadth-first search 25:32 - Estimating the distance from A to B in Big O 26:15 - Estimating the maximum queue size in breadth-first search (BFS) 27:34 - Back to estimation from memory 27:56 - Finding the shortest route 28:25 - Modifying BFS for route finding 28:42 - Looking at the code (Python) 29:42 - Understanding path recovery 30:45 - Java, JavaScript, C++, Go: Shortest Path Recovery 30:52 - Estimating Time and Memory in Big O 31:32 - Chilling 32:45 - Creating a Quick Response System 33:40 - How to Solve the Problem of Multiple Breadth-First Search Runs 34:30 - Implementing Multi-Source BFS (Python) 35:32 - Java, JavaScript, C++, Go: Multi-Source BFS 35:43 - Is Multi-Source BFS Really Necessary? 36:02 - Alternative Solution Code (Python) 36:07 - Java, JavaScript, C++, Go 36:18 - Comparing Solution Options 36:40 - When to Use Breadth-First Search vs. Depth-First Search (BFS vs. DFS) 37:18 - Why Use DFS When You Have BFS 37:42 - How Graph Problems Are Solved in Interviews 38:09 - How I Present My Solution Idea in an Interview 39:18 - How to Strengthen Your Competitive Advantage 🔥 PRACTICE AND INTERVIEW PREPARATION: Graph Practice and Preparation for Algorithmic Interviews: https://clck.ru/3RAkSo ⚠️ A promo code for a discount is available at the link! The final terms of the promo code are subject to change and are always displayed on the website. 📱 MY TELEGRAM CHANNEL: https://t.me/algocode_algorithms Here I share additional materials, problem analysis, and announcements of new videos. Subscribe! For mini-groups, write to Telegram: fatinmaks Advertising. Individual Entrepreneur Fatin. Taxpayer Identification Number: 525406426719. Erid: 2Vtzqv9yRzv