Practice Subproblem Dependency (4.4) - Longest Common Subsequence - Design & Analysis of Algorithms

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6 sample questions

Question 1.
Define Longest Common Subsequence in your own words.
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Think about patterns in sequences.
Question 2.
What is dynamic programming?
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Consider how problems can be simplified.
3Question 3.
What is the time complexity of finding LCS using dynamic programming?
- O(m*n)
- O(m+n)
- O(m^2)
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Remember how we build the solution.
4Question 4.
True or False: LCS can include characters that are not adjacent in given sequences.
- True
- False
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Think about the definition of a subsequence.
Question 5.
Suppose you have string A: 'ABCBDAB' and string B: 'BDCAB'. Calculate the LCS, and provide the DP table.
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Start with filling the first two rows based on matches and mismatches.
Question 6.
Discuss how LCS can be extended to more than two sequences. What complexities arise?
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Consider expanding the dimension of the DP table for more sequences.

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