Get Equal Substrings Within Budget | Classic Sliding Window | Leetcode 1208 | codestorywithMIK

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Published on May 27, 2024 12:00:00 AM ● Video Link: https://www.youtube.com/watch?v=MF2MgJQuFhA

Duration: 20:09

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This is the 21st Video of our Playlist "Sliding Window : Popular Interview Problems" by codestorywithMIK

In this video we will try to solve a good and classic Sliding Window Problem : Get Equal Substrings Within Budget | Classic Sliding Window | Thought Process | Leetcode 1208 | codestorywithMIK

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 : Get Equal Substrings Within Budget | Classic Sliding Window | Thought Process | Leetcode 1208 | codestorywithMIK
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My solutions on Github(C++ & JAVA) : https://github.com/MAZHARMIK/Intervie...
Leetcode Link : https://leetcode.com/problems/get-equ...


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Summary :
The `equalSubstring` function takes two strings `s` and `t` of the same length, along with an integer `maxCost`. It aims to find the maximum length of a substring within `s` where the total cost of converting characters from `s` to `t` does not exceed `maxCost`.
The approach uses a sliding window technique. It iterates through the strings `s` and `t` simultaneously, tracking the cost of converting characters as it moves along. Whenever the total cost exceeds `maxCost`, the algorithm shrinks the window from the left end until the cost is within the allowed limit.
During each iteration, the algorithm updates the maximum length of the valid substring encountered so far. Finally, it returns the maximum length found.
Overall, the approach efficiently finds the maximum length of a valid substring by dynamically adjusting the window based on the cost constraint.

✨ Timelines✨
00:00 - Introduction

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