Longest Common Subsequence (2 Strings) - Dynamic Programming & Competing Subproblems
Code & Problem Statement @ https://backtobackswe.com/platform/co...
Free 5-Day Mini-Course: https://backtobackswe.com
Try Our Full Platform: https://backtobackswe.com/pricing
📹 Intuitive Video Explanations
🏃 Run Code As You Learn
💾 Save Progress
❓New Unseen Questions
🔎 Get All Solutions
Question: You are given 2 strings. Return the length of the longest subsequence that the 2 strings share.
Complexities
n = s1.length()
m = s2.length()
Time: O( nm )
We can upper bound time by the number of subproblems that we are going to solve.
Space: O( nm )
We upper bound space by the number of subproblems we will story answers to. Whether we do (n + 1)(m + 1) or (n)(m) doesn't matter asymptotically.
++++++++++++++++++++++++++++++++++++++++++++++++++
HackerRank: / @hackerrankofficial
Tuschar Roy: / tusharroy2525
GeeksForGeeks: / @geeksforgeeksvideos
Jarvis Johnson: / vsympathyv
Success In Tech: / @successintech
Watch video Longest Common Subsequence (2 Strings) - Dynamic Programming & Competing Subproblems online without registration, duration hours minute second in high quality. This video was added by user Back To Back SWE 14 February 2019, don't forget to share it with your friends and acquaintances, it has been viewed on our site 197,122 once and liked it 8.6 thousand people.