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Grokking Dynamic Programming Interview

Palindromic Partitioning

Explore techniques to partition a string into the minimum number of palindromic substrings. This lesson guides you through naive recursive solutions and then shows how to optimize them using dynamic programming approaches including memoization and tabulation, helping you understand the time and space trade-offs involved.

We'll cover the following...

Statement

Suppose you are given a string, s. You need to perform the minimum number of cuts to divide the string into substrings, such that all the resulting substrings are palindromes.

Let’s say you have the following string:

  • “apple”

The resulting substrings after performing the minimum number of cuts are:

  • “a”∣|“pp”∣|“l”∣|“e”

So, a minimum of 33 cuts are required.

Constraints:

  • 1≤1 \leq s.length ≤1.5×103\leq 1.5\times10^3
  • s consists of only lowercase English characters.

Examples

No.

s

cuts

1

"sleek"

3

2

"adjacent"

7

3

"radar"

0

Try it yourself

Implement your solution in the ...

Java
usercode > MinCuts.java
import java.util.*;
public class MinCuts {
   public static int minCuts(String arr) {
      // Write your code here
         
      return -1;
   }
}
Palindromic Partitioning

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