Out of Boundary Paths | Recursion | Memoization | Bottom Up | Optimal Bottom Up | Leetcode 576
0iPad PDF Notes - https://github.com/MAZHARMIK/Interview_DS_Algo/blob/master/iPad%20PDF%20Notes/Leetcode-576-Out%20of%20Boundary%20Paths.pdf
Whatsapp Community Link : https://www.whatsapp.com/channel/0029Va6kVSjICVfiVdsHgi1A
This is the 82nd Video of our Playlist "Dynamic Programming : Popular Interview Problems".
In this video we will try to solve a very good DP problem - Count the Number of Houses at a Certain Distance I (Leetcode 576)
I will explain the intuition so easily that you will never forget and start seeing this as cakewalk EASYYY.
We will do live coding after explanation and see if we are able to pass all the test cases.
Also, please note that my Github solution link below contains both C++ as well as JAVA code.
Problem Name : Out of Boundary Paths | Recursion | Memoization | Bottom Up | Optimal Bottom Up | Leetcode 576
Company Tags : Baidu, Amazon
My solutions on Github(C++ & JAVA) : https://github.com/MAZHARMIK/Interview_DS_Algo/blob/master/DP/Out%20of%20Boundary%20Paths.cpp
Leetcode Link : https://leetcode.com/problems/out-of-boundary-paths/description
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
Subscribe to my channel : https://www.youtube.com/@codestorywithMIK
Instagram : https://www.instagram.com/codestorywithmik/
Facebook : https://www.facebook.com/people/codestorywithmik/100090524295846/
Twitter : https://twitter.com/CSwithMIK
Approach-1 Summary : The solution uses dynamic programming with memoization to avoid redundant computations. The solve function recursively explores all possible paths from the starting cell within the given constraints and updates a 3D array t to store the results for previously calculated states. The findPaths function initializes the memoization array and calls the solve function to obtain the final result. The modulo operation is applied to avoid integer overflow. Overall, the approach employs a depth-first search with memoization to efficiently compute the number of paths satisfying the specified conditions in the grid.
Approach-2 Summary : The findPaths function initializes a 3D array dp of size 50x50x51 to store the number of possible moves leading to a path out of the boundary for each position and the remaining number of moves. The triple loop iterates over the number of moves, row indices, and column indices, updating the values in the dp array based on the possible moves in the four directions. The crucial difference is that, instead of recursively exploring the paths, the solution directly calculates the number of moves for each cell and move count from the bottom up, using the results of the previous iteration. The final result is obtained from the dp array at the starting position and with the maximum number of moves. This approach is more efficient than the recursive approach with memoization, as it avoids function call overhead and directly calculates the dynamic programming states iteratively.
Approach-3 Summary : The main idea is to iterate through the number of moves (maxMove) and update the t vector in each iteration. The nested loops iterate over the rows and columns of the grid, and for each cell, the code considers the possible moves in the four directions. If a move goes out of bounds, the value at that cell in the t vector is added to the result. Otherwise, the value is updated in a temporary 2D vector temp. At the end of each iteration, the t vector is updated with the values from the temp vector. The result is the sum of the values in the t vector corresponding to the starting position after the specified number of moves. This approach essentially simulates the movement of the paths in the grid over multiple iterations and accumulates the counts for reaching each cell. The result is the total number of paths that exit the grid within the given constraints.
╔═╦╗╔╦╗╔═╦═╦╦╦╦╗╔═╗
║╚╣║║║╚╣╚╣╔╣╔╣║╚╣═╣
╠╗║╚╝║║╠╗║╚╣║║║║║═╣
╚═╩══╩═╩═╩═╩╝╚╩═╩═╝
✨ Timelines✨
00:00 - Introduction
#coding #helpajobseeker #easyrecipes #leetcode #leetcodequestionandanswers #leetcodesolution #leetcodedailychallenge #leetcodequestions #leetcodechallenge #hindi #india #coding #helpajobseeker #easyrecipes #leetcode #leetcodequestionandanswers #leetcodesolution #leetcodedailychallenge#leetcodequestions #leetcodechallenge #hindi #india #hindiexplanation #hindiexplained #easyexplaination #interview#interviewtips #interviewpreparation #interview_ds_algo #hinglish #github #design #data #google #video #instagram #facebook #leetcode #computerscience #leetcodesolutions #leetcodequestionandanswers #code #learning #dsalgo #dsa #2024 #newyear