Practice Python Implementation And Efficiency (43.1.5) - Longest common subsequence - Part B
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Python Implementation and Efficiency

Practice - Python Implementation and Efficiency

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What do you initialize the first row and column of the LCS table to?

💡 Hint: Think about the base cases in DP.

Question 2 Easy

Why is dynamic programming more efficient than recursion for LCS?

💡 Hint: Consider the overlap in recursive calls.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the purpose of dynamic programming?

To solve problems only using recursion
To solve problems by breaking them into subproblems
To avoid using memory

💡 Hint: Consider the definition of dynamic programming.

Question 2

True or False: Each entry in the LCS table relies only on one previous cell.

True
False

💡 Hint: Think about how many directions we check.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Suppose you have two sequences: 'ABCBDAB' and 'BDCAB'. Calculate the LCS using dynamic programming and show the filled table.

💡 Hint: Pay attention to dependencies and relationships between characters.

Challenge 2 Hard

Design an algorithm to count how many different LCS can be formed from the sequences 'AGGTAB' and 'GXTXAYB'.

💡 Hint: Modify the LCS to return counts at each stage.

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Reference links

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