Which dynamic programming technique is used to solve the Longest Common Subseque

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Question: Which dynamic programming technique is used to solve the Longest Common Subsequence problem?

Options:

Correct Answer: Bottom-up

Solution:

The Longest Common Subsequence problem is typically solved using the bottom-up dynamic programming technique.

Which dynamic programming technique is used to solve the Longest Common Subsequence problem?

Which dynamic programming technique is used to solve the Longest Common Subsequence problem?

Step 1: Understand the Longest Common Subsequence (LCS) problem. It involves finding the longest sequence that appears in the same order in two different sequences, but not necessarily consecutively.
Step 2: Recognize that dynamic programming is a method used to solve problems by breaking them down into simpler subproblems and storing the results of these subproblems to avoid redundant calculations.
Step 3: Identify the bottom-up approach in dynamic programming. This means starting from the simplest subproblems and building up to the solution of the main problem.
Step 4: In the context of LCS, create a table (2D array) where each cell represents the length of the LCS for different prefixes of the two sequences.
Step 5: Fill in the table by comparing characters from both sequences and using previously computed values to determine the length of the LCS.
Step 6: The value in the bottom-right cell of the table will give you the length of the longest common subsequence.

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