Practice Dynamic Programming (1.3.3) - Design and Analysis of Algorithms

Practice: Dynamic Programming

Lesson 1.3.3Design and Analysis of Algorithms

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9 questions

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6 sample questions

Question 1.
What is Dynamic Programming in your own words?
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Think of solving a large puzzle piece by piece.
Question 2.
Define Memoization.
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Consider how you remember the answers to previously solved problems.
3Question 3.
What is the main benefit of using Dynamic Programming?
- It speeds up all algorithms
- It saves computational resources by avoiding repeated calculations
- It simplifies all problems
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Think about the problems DP was designed to solve.
4Question 4.
True or False: Dynamic Programming is only effective for problems with optimal substructure.
- True
- False
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Consider how solutions are constructed in DP.
Question 5.
Given a list of coin denominations, devise a dynamic programming algorithm to determine the minimum number of coins required to make a specific amount.
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Start by filling the base cases and build upwards.
Question 6.
Implement a dynamic programming solution for the Edit Distance problem, which finds the minimum number of edits required to convert one string into another.
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Consider insertions, deletions, and substitutions at each step.

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