Rat in a Maze Problem | Simple Story To Code | Recursion Concepts And Questions | Video 11
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This is the 11th video of our playlist "Recursion Concepts And Questions". Find the Details below :
Video Name : Rat in a Maze Problem | Simple Story To Code | Recursion Concepts And Questions
Video # : 11
C++/Java Code Link : https://github.com/MAZHARMIK/Interview_DS_Algo/blob/master/Recursion/Rat%20in%20a%20Maze%20Problem%20-%20I.cpp
GfG Problem Link : https://www.geeksforgeeks.org/problems/rat-in-a-maze-problem/1
๐ Unraveling Recursion: A Journey into the Depths of Code
๐ฅ Welcome to the 11th Video of my Recursion Playlist! ๐ In this enlightening video, we will solve a very famous recursion/backtracking problem "Rat in a Maze Problem" with the help of Recursion. We will start with a Simple story understanding the problem by making a simple tree Diagram and then we will be Converting Story to code and writing the recursive code for the problem and also I will also be explaining the Time and Space Complexity of the code ๐
๐ What's Inside?
๐ Simple story understanding with Choice Tree Diagram
๐ Converting Story to code and writing the recursive code for Rat in a Maze Problem
๐ Explanation of Time and Space Complexity of the code
๐ฉโ๐ป Who Should Watch?
This playlist is for everyone but best suited for Freshers who are new to Recursion.
๐ Embark on the Recursive Adventure Now!
My DP Concepts Playlist : https://youtu.be/7eLMOE1jnls
My Graph Concepts Playlist : https://youtu.be/5JGiZnr6B5w
My GitHub Repo for interview preparation : https://github.com/MAZHARMIK/Interview_DS_Algo
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Approach Summary : The solve function explores all valid moves (up, down, left, right) from each cell, marking visited cells and backtracking when necessary. The base case is reaching the destination cell, at which point the current path is added to the result. The algorithm explores all possible paths) from each cell forming the path in a temp string. As we reach the base case, we store the path if we reach (n-1, n-1). While conceptually simple, this approach can be computationally expensive for large grid sizes.
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โจ Timelinesโจ
00:00 - Introduction
00:12 - Motivation (Bhashan)
01:08 - Understand Problem
05:31 - Thought Process
05:55 - Tree Diagram
17:12 - Code Trust in Recursion
31:45 - Time Complexity
35:13 - Space Complexity
37:22 - Coding it up
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