Dynamic Programming

Dynamic programming is a powerful technique used to solve optimization problems by breaking them down into smaller overlapping subproblems and solving each subproblem only once. It is an efficient way to solve problems and can significantly reduce the time complexity.

In the context of the Longest Common Subsequence problem, dynamic programming can be used to find the length of the longest common subsequence between two strings. By using a dynamic programming approach, we can avoid redundant calculations and solve the problem in a more efficient manner.

The basic idea behind dynamic programming is to store the solutions to subproblems in a table and use those solutions to solve larger subproblems. This allows us to avoid repeating calculations and quickly find the optimal solution.

Let's take a closer look at how dynamic programming can be applied to the Longest Common Subsequence problem.