LeetCode 1143 Revision | Print All Distinct LCS | C++ & Java
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In this video, we extend LeetCode 1143 - Longest Common Subsequence (LCS) and solve the classic variant:
LCS Original : • LeetCode 1143 Revision | Longest Common Su...
*Print All Distinct Longest Common Subsequences.*
Instead of only finding the length of the LCS, we learn how to recover every distinct LCS string from the DP table.
This is one of the most important follow-up questions in interviews and contests, because many students know how to fill the DP table but struggle with backtracking and collecting all valid answers without duplicates.
We focus on one key idea:
*Once the LCS length DP table is built, how do we backtrack through it to generate every distinct LCS string?*
References :
1) Nitin Saxena Sir Notes
https://www.cse.iitk.ac.in/users/niti...
2) IIT Kharagpur Notes
https://facweb.iitkgp.ac.in/~sourav/L...
3) MaryLand University Notes
https://www.cs.umd.edu/class/spring20...
Topics Covered:
• Problem Explanation
• Difference Between LCS Length and Printing All LCS
• Understanding Distinct Subsequences
• DP State Definition for LCS Length
• Building the LCS DP Table
• Why Multiple LCS Strings Can Exist
• Backtracking Through the DP Table
• When to Move Up, Left, or Diagonally
• Recursive Backtracking Solution
• Collecting Distinct Answers Using a Set
• Why a Set Is Needed
• Memoization for Backtracking
• Tabulation + Backtracking Approach
• C++ Solution
• Java Solution
• Time Complexity
• Space Complexity
By the end of this video, you'll understand how to move from "find LCS length" to "print all distinct LCS strings", which makes it much easier to solve LCS backtracking variants in interviews and contests.
Hunter Coding focuses on:
• DSA Revision
• Curated Problem Solutions
• OA Preparation
• Interview Strategy
Revise Patterns, Not Solutions.
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