Practice Dynamic Programming (13.3.4) - Implementation of Algorithms to Solve Problems

Practice: Dynamic Programming

Lesson 13.3.4Implementation of Algorithms to Solve Problems

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9 questions

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6 sample questions

Question 1.
What does dynamic programming do?
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Think about solving problems incrementally.
Question 2.
Define overlapping sub-problems in your own words.
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Consider the Fibonacci example.
3Question 3.
What is Dynamic Programming?
- A way to write simulations
- A technique to solve problems by breaking them down
- An optimization for data storage
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Think about how complex problems can be decomposed for easier solutions.
4Question 4.
True or False: Dynamic Programming uses memoization to store results of sub-problems?
- True
- False
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Remember the Fibonacci example where results were stored.
Question 5.
Create a dynamic programming algorithm to solve the longest common subsequence problem between two strings.
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Think of tracking matches step by step and keep expressing lengths.
Question 6.
Devise a dynamic programming approach to count the number of ways to climb to the top of a staircase with 'n' steps when you can take either 1 or 2 steps at a time.
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Start with the smallest steps and build up!

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