Preparing Dynamic Programming for your next tech interview in 2022

Problems on Dynamic Programming for Coding Interviews 

1. 0-1 Knapsack 
2. Min binary Partition 
3. Shortest Common Supersequence 
4. Colorful Knapsack 
5. Maximum Subarray Sum 
6. Longest Increasing Subsequence 
7. Rod Cutting Problem 
8. Partition to K equal subsets 
9. Ways to arrange Balls
10. Longest Palindromic Subsequence  
11. Minimum Cost to buy N items
12. Painting Fences Problem
13. And many, many more….  

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Cracking the Dynamic Programming Coding Interview 

A consistent process for arriving at the best DP solution can give you an advantage over your competition. The FAST Dynamic Programming approach does exactly that. The FAST technique involves four steps, as the name suggests:

• Find the first answer.
• Analyze the first option.
• Subproblems must be identified.
• Turn the problem around.

Using the FAST technique can help you breeze through your coding interview when handling DP issues.

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Frequently Asked Questions

Is Dynamic Programming capable of solving all issues?

No, DP cannot address all issues. The DP method can be used if the problem has optimum substructure and overlapping sub-problems.

What are the two most important characteristics for a problem to be suitable for dynamic programming?

The two most important characteristics for DP to work are optimum substructure and overlapping sub-problems. The divide and conquer method is used when a solution to a problem can be discovered by combining optimum solutions to non-overlapping sub-problems.

What disadvantages does dynamic programming have over recursion? 

Some disadvantages of dynamic programming over recursion include the need for a large amount of memory to keep the estimated outcome of each subproblem. It's impossible to say if all saved values will be used. Frequently, the cached result is never used in later subproblems.

What is the significance of dynamic programming?

The DP approach aids us in efficiently solving tough situations. It is so widely used in academia, business, and top software engineering interviews.

What is the difference between dynamic programming and recursion?

Recursion is a technique for solving optimum substructure problems and maybe split down into comparable subproblems.

Conclusion 

In this article, we will discuss in brief what is a dynamic programming algorithm, how to approach problems on dynamic programming in interviews, and what are the different types of dynamic programming questions are asked in the interview. 

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