Longest Common Subsequence Problem Using Dynamic Programming | Data Structures | Simplilearn

Longest Common Subsequence Problem Using Dynamic Programming | Data Structures | Simplilearn

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This video on Longest Common Subsequence Problem Using Dynamic Programming will acquaint you with a clear understanding of the LCS problem statement and solution implementation. In this Data Structure Tutorial, you will understand why a recursive solution for an LCS problem is not compatible and how you can solve the same problem with less time complexity using DP. Finally, we will cover the dynamic programming implementation of the Longest Common Subsequence Problem.

00:00 Introduction
01:04 What Is Longest Common Subsequence
06:34 Longest Common Subsequence Using Recursion
14:03 LCS Implementation Using Dynamic Programming

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What Is Dynamic Programming?
In computer science, something is said to be efficient if it is quick and uses minimal memory. By storing the solutions to subproblems, we can quickly look them up if the same problem arises again. Because there is no need to recompute the solution, this saves a significant amount of calculation time. But hold on! Efficiency comprises both time and space difficulty. But, why does it matter if we reduce the time required to solve the problem only to increase the space required? This is why it is critical to realize that the ultimate goal of Dynamic Programming is to obtain considerably quicker calculation time at the price of a minor increase in space utilized. Dynamic programming is defined as an algorithmic paradigm that solves a given complex problem by breaking it into several sub-problems and storing the results of those sub-problems to avoid the computation of the same sub-problem over and over again.

What is Programming?
Programming is an act of designing, developing, deploying an executlable software solution to the given user-defined problem.
Programming involves the following stages.
– Problem Statement
– Algorithms and Flowcharts
– Coding the program
– Debug the program.
– Documention
– Maintainence

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Longest Common Subsequence Problem Using Dynamic Programming | Data Structures | Simplilearn