String Compression II | Recursion | 2-D Memoization | Leetcode 1531

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Published on ● Video Link: https://www.youtube.com/watch?v=Br3MiKmZRnc


Duration: 31:49
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This is the 78th Video of our Playlist "Dynamic Programming : Popular Interview Problems".
In this video we will try to solve a very good DP problem - String Compression II (Leetcode 1531).
We had already solved it using Recursion Memoization in the 77th video using 4-D Memoization and in this video, I have explained the 2-D Memoization approach.

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 : String Compression II
Company Tags : Adobe, Microsoft, Uber
My solutions on Github(C++ & JAVA) : https://github.com/MAZHARMIK/Interview_DS_Algo/blob/master/strings/String%20Compression%20II.cpp
Leetcode Link : https://leetcode.com/problems/string-compression-ii/

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 code recursively explores deletion and keeping options, memoizing results to avoid redundant calculations. Base cases handle invalid scenarios, and the final result is obtained using memoization. The getLengthOfOptimalCompression method initializes variables and calls solve to find the optimal compression length for the entire string.

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✨ Timelines✨
00:00 - Introduction

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