Practice Python Implementation and Efficiency - 43.1.5 | 43. Longest common subsequence - Part B | Data Structures and Algorithms in Python
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43.1.5 - Python Implementation and Efficiency

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

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

πŸ’‘ Hint: Think about the base cases in DP.

Question 2

Easy

Why is dynamic programming more efficient than recursion for LCS?

πŸ’‘ Hint: Consider the overlap in recursive calls.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

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

πŸ’‘ 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

πŸ’‘ Hint: Think about how many directions we check.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

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

πŸ’‘ Hint: Pay attention to dependencies and relationships between characters.

Question 2

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

πŸ’‘ Hint: Modify the LCS to return counts at each stage.

Challenge and get performance evaluation