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Longest repeating and non-overlapping substring

Last Updated : 16 Nov, 2024
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Given a string s, the task is to find the longest repeating non-overlapping substring in it. In other words, find 2 identical substrings of maximum length which do not overlap. Return -1 if no such string exists.

Note: Multiple Answers are possible but we have to return the substring whose first occurrence is earlier.

Examples: 

Input: s = “acdcdacdc”
Output: “acdc”
Explanation: The string “acdc” is the longest Substring of s which is repeating but not overlapping.

Input: s = “geeksforgeeks”
Output: “geeks”
Explanation: The string “geeks” is the longest subString of s which is repeating but not overlapping.

Table of Content

  • Using Brute Force Method – O(n^3) Time and O(n) Space
  • Using Top-Down DP (Memoization) – O(n^2) Time and O(n^2) Space
  • Using Bottom-Up DP (Tabulation) – O(n^2) Time and O(n^2) Space
  • Using Space Optimized DP – O(n^2) Time and O(n) Space

Using Brute Force Method – O(n^3) Time and O(n) Space

The idea is to generate all the possible substrings and check if the substring exists in the remaining string. If substring exists and its length is greater than answer substring, then set answer to current substring.

C++
// C++ program to find longest repeating // and non-overlapping substring // using recursion #include <bits/stdc++.h> using namespace std;  string longestSubstring(string& s) {     int n = s.length();      string ans = "";     int len = 0;      int i = 0, j = 0;      while (i < n && j < n) {          string curr = s.substr(i, j - i + 1);          // If substring exists, compare its length         // with ans         if (s.find(curr, j + 1) != string::npos              && j - i + 1 > len) {             len = j - i + 1;             ans = curr;         }          // Otherwise increment i         else             i++;          j++;     }      return len > 0 ? ans : "-1"; }  int main() {     string s = "geeksforgeeks";     cout << longestSubstring(s) << endl;     return 0; } 
Java
// Java program to find longest repeating // and non-overlapping substring // using recursion class GfG {      static String longestSubstring(String s) {         int n = s.length();          String ans = "";         int len = 0;          int i = 0, j = 0;          while (i < n && j < n) {              String curr = s.substring(i, j + 1);              // If substring exists, compare its length             // with ans             if (s.indexOf(curr, j + 1) != -1                 && j - i + 1 > len) {                 len = j - i + 1;                 ans = curr;             }              // Otherwise increment i             else                 i++;              j++;         }          return len > 0 ? ans : "-1";     }      public static void main(String[] args) {         String s = "geeksforgeeks";         System.out.println(longestSubstring(s));     } } 
Python
# Python program to find longest repeating # and non-overlapping substring # using recursion  def longestSubstring(s):     n = len(s)      ans = ""     lenAns = 0      i, j = 0, 0      while i < n and j < n:          curr = s[i:j + 1]          # If substring exists, compare its length         # with ans         if s.find(curr, j + 1) != -1 and j - i + 1 > lenAns:             lenAns = j - i + 1             ans = curr          # Otherwise increment i         else:             i += 1          j += 1      if lenAns > 0:         return ans     return "-1"   if __name__ == "__main__":     s = "geeksforgeeks"     print(longestSubstring(s)) 
C#
// C# program to find longest repeating // and non-overlapping substring // using recursion  using System;  class GfG {      static string longestSubstring(string s) {         int n = s.Length;          string ans = "";         int len = 0;          int i = 0, j = 0;          while (i < n && j < n) {              string curr = s.Substring(i, j - i + 1);              // If substring exists, compare its length             // with ans             if (s.IndexOf(curr, j + 1) != -1                 && j - i + 1 > len) {                 len = j - i + 1;                 ans = curr;             }              // Otherwise increment i             else                 i++;              j++;         }          return len > 0 ? ans : "-1";     }      static void Main(string[] args) {         string s = "geeksforgeeks";         Console.WriteLine(longestSubstring(s));     } } 
JavaScript
// JavaScript program to find longest repeating // and non-overlapping substring // using recursion  function longestSubstring(s) {     const n = s.length;      let ans = "";     let len = 0;      let i = 0, j = 0;      while (i < n && j < n) {          const curr = s.substring(i, j + 1);          // If substring exists, compare its length         // with ans         if (s.indexOf(curr, j + 1) !== -1             && j - i + 1 > len) {             len = j - i + 1;             ans = curr;         }          // Otherwise increment i         else             i++;          j++;     }      return len > 0 ? ans : "-1"; }  const s = "geeksforgeeks"; console.log(longestSubstring(s)); 

Output
geeks 

Using Top-Down DP (Memoization) – O(n^2) Time and O(n^2) Space

The approach is to compute the longest repeating suffix for all prefix pairs in the string s. For indices i and j, if s[i] == s[j], then recursively compute suffix(i+1, j+1) and set suffix(i, j) as min(suffix(i+1, j+1) + 1, j – i – 1) to prevent overlap. If the characters do not match, set suffix(i, j) = 0.

Note:

  • To avoid overlapping we have to ensure that the length of suffix is less than (j-i) at any instant. 
  • The maximum value of suffix(i, j) provides the length of the longest repeating substring and the substring itself can be found using the length and the starting index of the common suffix.
  • suffix(i, j) stores the length of the longest common suffix between indices i and j, ensuring it doesn’t exceed j – i – 1 to avoid overlap.
C++
// C++ program to find longest repeating // and non-overlapping substring // using memoization #include <bits/stdc++.h> using namespace std;  int findSuffix(int i, int j, string &s,                 vector<vector<int>> &memo) {      // base case     if (j == s.length())         return 0;      // return memoized value     if (memo[i][j] != -1)         return memo[i][j];      // if characters match     if (s[i] == s[j]) {         memo[i][j] = 1 + min(findSuffix(i + 1, j + 1, s, memo),                              j - i - 1);     }     else {         memo[i][j] = 0;     }      return memo[i][j]; }  string longestSubstring(string s) {      int n = s.length();      vector<vector<int>> memo(n, vector<int>(n, -1));      // find length of non-overlapping     // substrings for all pairs (i,j)     for (int i = 0; i < n; i++) {         for (int j = i + 1; j < n; j++) {             findSuffix(i, j, s, memo);         }     }      string ans = "";     int ansLen = 0;      // If length of suffix is greater     // than ansLen, update ans and ansLen     for (int i = 0; i < n; i++) {         for (int j = i + 1; j < n; j++) {             if (memo[i][j] > ansLen) {                 ansLen = memo[i][j];                 ans = s.substr(i, ansLen);             }         }     }      return ansLen > 0 ? ans : "-1"; }  int main() {     string s = "geeksforgeeks";     cout << longestSubstring(s) << endl;     return 0; } 
Java
// Java program to find longest repeating // and non-overlapping substring // using memoization import java.util.Arrays;  class GfG {      static int findSuffix(int i, int j, String s,                           int[][] memo) {          // base case         if (j == s.length())             return 0;          // return memoized value         if (memo[i][j] != -1)             return memo[i][j];          // if characters match         if (s.charAt(i) == s.charAt(j)) {             memo[i][j] = 1                          + Math.min(findSuffix(i + 1, j + 1,                                                s, memo),                                     j - i - 1);         }         else {             memo[i][j] = 0;         }          return memo[i][j];     }      static String longestSubstring(String s) {          int n = s.length();          int[][] memo = new int[n][n];         for (int[] row : memo) {             Arrays.fill(row, -1);         }          // find length of non-overlapping         // substrings for all pairs (i, j)         for (int i = 0; i < n; i++) {             for (int j = i + 1; j < n; j++) {                 findSuffix(i, j, s, memo);             }         }          String ans = "";         int ansLen = 0;          // If length of suffix is greater         // than ansLen, update ans and ansLen         for (int i = 0; i < n; i++) {             for (int j = i + 1; j < n; j++) {                 if (memo[i][j] > ansLen) {                     ansLen = memo[i][j];                     ans = s.substring(i, i + ansLen);                 }             }         }          return ansLen > 0 ? ans : "-1";     }      public static void main(String[] args) {         String s = "geeksforgeeks";         System.out.println(longestSubstring(s));     } } 
Python
# Python program to find longest repeating # and non-overlapping substring # using memoization  def findSuffix(i, j, s, memo):      # base case     if j == len(s):         return 0      # return memoized value     if memo[i][j] != -1:         return memo[i][j]      # if characters match     if s[i] == s[j]:         memo[i][j] = 1 + min(findSuffix(i + 1, j + 1, s, memo), \                              j - i - 1)     else:         memo[i][j] = 0      return memo[i][j]   def longestSubstring(s):     n = len(s)      memo = [[-1] * n for _ in range(n)]      # find length of non-overlapping     # substrings for all pairs (i, j)     for i in range(n):         for j in range(i + 1, n):             findSuffix(i, j, s, memo)      ans = ""     ansLen = 0      # If length of suffix is greater     # than ansLen, update ans and ansLen     for i in range(n):         for j in range(i + 1, n):             if memo[i][j] > ansLen:                 ansLen = memo[i][j]                 ans = s[i:i + ansLen]      if ansLen > 0:         return ans      return "-1"   if __name__ == "__main__":     s = "geeksforgeeks"     print(longestSubstring(s)) 
C#
// C# program to find longest repeating // and non-overlapping substring // using memoization  using System;  class GfG {      static int findSuffix(int i, int j, string s,                           int[, ] memo) {          // base case         if (j == s.Length)             return 0;          // return memoized value         if (memo[i, j] != -1)             return memo[i, j];          // if characters match         if (s[i] == s[j]) {             memo[i, j] = 1                          + Math.Min(findSuffix(i + 1, j + 1,                                                s, memo),                                     j - i - 1);         }         else {             memo[i, j] = 0;         }          return memo[i, j];     }      static string longestSubstring(string s) {         int n = s.Length;          int[, ] memo = new int[n, n];         for (int i = 0; i < n; i++) {             for (int j = 0; j < n; j++) {                 memo[i, j] = -1;             }         }          // find length of non-overlapping         // substrings for all pairs (i, j)         for (int i = 0; i < n; i++) {             for (int j = i + 1; j < n; j++) {                 findSuffix(i, j, s, memo);             }         }          string ans = "";         int ansLen = 0;          // If length of suffix is greater         // than ansLen, update ans and ansLen         for (int i = 0; i < n; i++) {             for (int j = i + 1; j < n; j++) {                 if (memo[i, j] > ansLen) {                     ansLen = memo[i, j];                     ans = s.Substring(i, ansLen);                 }             }         }          return ansLen > 0 ? ans : "-1";     }      static void Main(string[] args) {         string s = "geeksforgeeks";         Console.WriteLine(longestSubstring(s));     } } 
JavaScript
// JavaScript program to find longest repeating // and non-overlapping substring // using memoization  function findSuffix(i, j, s, memo) {      // base case     if (j === s.length)         return 0;      // return memoized value     if (memo[i][j] !== -1)         return memo[i][j];      // if characters match     if (s[i] === s[j]) {         memo[i][j]             = 1               + Math.min(findSuffix(i + 1, j + 1, s, memo),                          j - i - 1);     }     else {         memo[i][j] = 0;     }      return memo[i][j]; }  function longestSubstring(s) {     const n = s.length;      const memo         = Array.from({length : n}, () => Array(n).fill(-1));      // find length of non-overlapping     // substrings for all pairs (i, j)     for (let i = 0; i < n; i++) {         for (let j = i + 1; j < n; j++) {             findSuffix(i, j, s, memo);         }     }      let ans = "";     let ansLen = 0;      // If length of suffix is greater     // than ansLen, update ans and ansLen     for (let i = 0; i < n; i++) {         for (let j = i + 1; j < n; j++) {             if (memo[i][j] > ansLen) {                 ansLen = memo[i][j];                 ans = s.substring(i, i + ansLen);             }         }     }      return ansLen > 0 ? ans : "-1"; }  const s = "geeksforgeeks"; console.log(longestSubstring(s)); 

Output
geeks 

Using Bottom-Up DP (Tabulation) – O(n^2) Time and O(n^2) Space

The idea is to create a 2D matrix of size (n+1)*(n+1) and calculate the longest repeating suffixes for all index pairs (i, j) iteratively. We start from the end of the string and work backwards to fill the table. For each (i, j), if s[i] == s[j], we set suffix[i][j] to min(suffix[i+1][j+1]+1, j-i-1) to avoid overlap; otherwise, suffix[i][j] = 0.

C++
// C++ program to find longest repeating // and non-overlapping substring // using tabulation #include <bits/stdc++.h> using namespace std;  string longestSubstring(string s) {      int n = s.length();     vector<vector<int>> dp(n+1, vector<int>(n+1, 0));          string ans = "";     int ansLen = 0;          // find length of non-overlapping      // substrings for all pairs (i,j)     for (int i=n-1; i>=0; i--) {         for (int j=n-1; j>i; j--) {                          // if characters match, set value              // and compare with ansLen.             if (s[i]==s[j]) {                 dp[i][j] = 1 + min(dp[i+1][j+1], j-i-1);                                  if (dp[i][j]>=ansLen) {                     ansLen = dp[i][j];                     ans = s.substr(i, ansLen);                 }             }         }     }          return ansLen>0?ans:"-1"; }  int main() { 	string s = "geeksforgeeks";     cout << longestSubstring(s) << endl; 	return 0; } 
Java
// Java program to find longest repeating // and non-overlapping substring // using tabulation   class GfG {      static String longestSubstring(String s) {          int n = s.length();         int[][] dp = new int[n + 1][n + 1];                  String ans = "";         int ansLen = 0;                  // find length of non-overlapping          // substrings for all pairs (i, j)         for (int i = n - 1; i >= 0; i--) {             for (int j = n - 1; j > i; j--) {                                  // if characters match, set value                  // and compare with ansLen.                 if (s.charAt(i) == s.charAt(j)) {                     dp[i][j] = 1 + Math.min(dp[i + 1][j + 1], j - i - 1);                                          if (dp[i][j] >= ansLen) {                         ansLen = dp[i][j];                         ans = s.substring(i, i + ansLen);                     }                 }             }         }                  return ansLen > 0 ? ans : "-1";     }      public static void main(String[] args) {         String s = "geeksforgeeks";         System.out.println(longestSubstring(s));     } } 
Python
# Python program to find longest repeating # and non-overlapping substring # using tabulation  def longestSubstring(s):     n = len(s)     dp = [[0] * (n + 1) for _ in range(n + 1)]          ans = ""     ansLen = 0          # find length of non-overlapping      # substrings for all pairs (i, j)     for i in range(n - 1, -1, -1):         for j in range(n - 1, i, -1):                          # if characters match, set value              # and compare with ansLen.             if s[i] == s[j]:                 dp[i][j] = 1 + min(dp[i + 1][j + 1], j - i - 1)                                  if dp[i][j] >= ansLen:                     ansLen = dp[i][j]                     ans = s[i:i + ansLen]          return ans if ansLen > 0 else "-1"  if __name__ == "__main__":     s = "geeksforgeeks"     print(longestSubstring(s)) 
C#
// C# program to find longest repeating // and non-overlapping substring // using tabulation  using System;  class GfG {      static string longestSubstring(string s) {         int n = s.Length;         int[,] dp = new int[n + 1, n + 1];                  string ans = "";         int ansLen = 0;                  // find length of non-overlapping          // substrings for all pairs (i, j)         for (int i = n - 1; i >= 0; i--) {             for (int j = n - 1; j > i; j--) {                                  // if characters match, set value                  // and compare with ansLen.                 if (s[i] == s[j]) {                     dp[i, j] = 1 + Math.Min(dp[i + 1, j + 1], j - i - 1);                                          if (dp[i, j] >= ansLen) {                         ansLen = dp[i, j];                         ans = s.Substring(i, ansLen);                     }                 }             }         }                  return ansLen > 0 ? ans : "-1";     }      static void Main(string[] args) {         string s = "geeksforgeeks";         Console.WriteLine(longestSubstring(s));     } } 
JavaScript
// JavaScript program to find longest repeating // and non-overlapping substring // using tabulation  function longestSubstring(s) {     const n = s.length;     const dp = Array.from({ length: n + 1 }, () => Array(n + 1).fill(0));          let ans = "";     let ansLen = 0;          // find length of non-overlapping      // substrings for all pairs (i, j)     for (let i = n - 1; i >= 0; i--) {         for (let j = n - 1; j > i; j--) {                          // if characters match, set value              // and compare with ansLen.             if (s[i] === s[j]) {                 dp[i][j] = 1 + Math.min(dp[i + 1][j + 1], j - i - 1);                                  if (dp[i][j] >= ansLen) {                     ansLen = dp[i][j];                     ans = s.substring(i, i + ansLen);                 }             }         }     }          return ansLen > 0 ? ans : "-1"; }  const s = "geeksforgeeks"; console.log(longestSubstring(s)); 

Output
geeks 

Using Space Optimized DP – O(n^2) Time and O(n) Space

The idea is to use a single 1D array instead of a 2D matrix by keeping track of only the “next row” values required to compute suffix[i][j]. Since each value suffix[i][j] depends only on suffix[i+1][j+1] in the row below, we can maintain the previous row’s values in a 1D array and update them iteratively for each row.

C++
// C++ program to find longest repeating // and non-overlapping substring // using space optimised #include <bits/stdc++.h> using namespace std;  string longestSubstring(string s) {      int n = s.length();     vector<int> dp(n+1,0);          string ans = "";     int ansLen = 0;          // find length of non-overlapping      // substrings for all pairs (i,j)     for (int i=n-1; i>=0; i--) {          for (int j=i; j<n; j++) {                          // if characters match, set value              // and compare with ansLen.             if (s[i]==s[j]) {                 dp[j] = 1 + min(dp[j+1], j-i-1);                                  if (dp[j]>=ansLen) {                     ansLen = dp[j];                     ans = s.substr(i, ansLen);                 }             }             else dp[j] = 0;         }     }          return ansLen>0?ans:"-1"; }  int main() { 	string s = "geeksforgeeks";     cout << longestSubstring(s) << endl; 	return 0; } 
Java
// Java program to find longest repeating // and non-overlapping substring // using space optimised  class GfG {      static String longestSubstring(String s) {          int n = s.length();         int[] dp = new int[n + 1];                  String ans = "";         int ansLen = 0;                  // find length of non-overlapping          // substrings for all pairs (i, j)         for (int i = n - 1; i >= 0; i--) {             for (int j = i; j < n; j++) {                                  // if characters match, set value                  // and compare with ansLen.                 if (s.charAt(i) == s.charAt(j)) {                     dp[j] = 1 + Math.min(dp[j + 1], j - i - 1);                                          if (dp[j] >= ansLen) {                         ansLen = dp[j];                         ans = s.substring(i, i + ansLen);                     }                 } else {                     dp[j] = 0;                 }             }         }                  return ansLen > 0 ? ans : "-1";     }      public static void main(String[] args) {         String s = "geeksforgeeks";         System.out.println(longestSubstring(s));     } } 
Python
# Python program to find longest repeating # and non-overlapping substring # using space optimised  def longestSubstring(s):     n = len(s)     dp = [0] * (n + 1)          ans = ""     ansLen = 0          # find length of non-overlapping      # substrings for all pairs (i, j)     for i in range(n - 1, -1, -1):         for j in range(i, n):                          # if characters match, set value              # and compare with ansLen.             if s[i] == s[j]:                 dp[j] = 1 + min(dp[j + 1], j - i - 1)                                  if dp[j] >= ansLen:                     ansLen = dp[j]                     ans = s[i:i + ansLen]             else:                 dp[j] = 0          return ans if ansLen > 0 else "-1"  if __name__ == "__main__":     s = "geeksforgeeks"     print(longestSubstring(s)) 
C#
// C# program to find longest repeating // and non-overlapping substring // using space optimised  using System;  class GfG {      static string longestSubstring(string s) {         int n = s.Length;         int[] dp = new int[n + 1];                  string ans = "";         int ansLen = 0;                  // find length of non-overlapping          // substrings for all pairs (i, j)         for (int i = n - 1; i >= 0; i--) {             for (int j = i; j < n; j++) {                                  // if characters match, set value                  // and compare with ansLen.                 if (s[i] == s[j]) {                     dp[j] = 1 + Math.Min(dp[j + 1], j - i - 1);                                          if (dp[j] >= ansLen) {                         ansLen = dp[j];                         ans = s.Substring(i, ansLen);                     }                 } else {                     dp[j] = 0;                 }             }         }                  return ansLen > 0 ? ans : "-1";     }      static void Main(string[] args) {         string s = "geeksforgeeks";         Console.WriteLine(longestSubstring(s));     } } 
JavaScript
// JavaScript program to find longest repeating // and non-overlapping substring // using space optimised  function longestSubstring(s) {     const n = s.length;     const dp = new Array(n + 1).fill(0);          let ans = "";     let ansLen = 0;          // find length of non-overlapping      // substrings for all pairs (i, j)     for (let i = n - 1; i >= 0; i--) {         for (let j = i; j < n; j++) {                          // if characters match, set value              // and compare with ansLen.             if (s[i] === s[j]) {                 dp[j] = 1 + Math.min(dp[j + 1], j - i - 1);                                  if (dp[j] >= ansLen) {                     ansLen = dp[j];                     ans = s.substring(i, i + ansLen);                 }             } else {                 dp[j] = 0;             }         }     }          return ansLen > 0 ? ans : "-1"; }  const s = "geeksforgeeks"; console.log(longestSubstring(s)); 

Output
geeks 

Related articles: 

  • Longest Common Substring


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  • Steps to solve a Dynamic Programming Problem
    Steps to solve a Dynamic programming problem:Identify if it is a Dynamic programming problem.Decide a state expression with the Least parameters.Formulate state and transition relationship.Apply tabulation or memorization.Step 1: How to classify a problem as a Dynamic Programming Problem? Typically,
    14 min read
  • Advanced Topics

    • Count Ways To Assign Unique Cap To Every Person
      Given n people and 100 types of caps labelled from 1 to 100, along with a 2D integer array caps where caps[i] represents the list of caps preferred by the i-th person, the task is to determine the number of ways the n people can wear different caps. Example: Input: caps = [[3, 4], [4, 5], [5]] Outpu
      15+ min read

    • Digit DP | Introduction
      Prerequisite : How to solve a Dynamic Programming Problem ?There are many types of problems that ask to count the number of integers 'x' between two integers say 'a' and 'b' such that x satisfies a specific property that can be related to its digits.So, if we say G(x) tells the number of such intege
      14 min read

    • Sum over Subsets | Dynamic Programming
      Prerequisite: Basic Dynamic Programming, Bitmasks Consider the following problem where we will use Sum over subset Dynamic Programming to solve it. Given an array of 2n integers, we need to calculate function F(x) = ?Ai such that x&i==i for all x. i.e, i is a bitwise subset of x. i will be a bit
      10 min read

    Easy problems in Dynamic programming

    • Coin Change - Count Ways to Make Sum
      Given an integer array of coins[] of size n representing different types of denominations and an integer sum, the task is to count all combinations of coins to make a given value sum. Note: Assume that you have an infinite supply of each type of coin. Examples: Input: sum = 4, coins[] = [1, 2, 3]Out
      15+ min read

    • Subset Sum Problem
      Given an array arr[] of non-negative integers and a value sum, the task is to check if there is a subset of the given array whose sum is equal to the given sum. Examples: Input: arr[] = [3, 34, 4, 12, 5, 2], sum = 9Output: TrueExplanation: There is a subset (4, 5) with sum 9. Input: arr[] = [3, 34,
      15+ min read

    • Introduction and Dynamic Programming solution to compute nCr%p
      Given three numbers n, r and p, compute value of nCr mod p. Example: Input: n = 10, r = 2, p = 13 Output: 6 Explanation: 10C2 is 45 and 45 % 13 is 6.We strongly recommend that you click here and practice it, before moving on to the solution.METHOD 1: (Using Dynamic Programming) A Simple Solution is
      15+ min read

    • Rod Cutting
      Given a rod of length n inches and an array price[]. price[i] denotes the value of a piece of length i. The task is to determine the maximum value obtainable by cutting up the rod and selling the pieces. Note: price[] is 1-indexed array. Input: price[] = [1, 5, 8, 9, 10, 17, 17, 20]Output: 22Explana
      15+ min read

    • Painting Fence Algorithm
      Given a fence with n posts and k colors, the task is to find out the number of ways of painting the fence so that not more than two consecutive posts have the same color. Examples: Input: n = 2, k = 4Output: 16Explanation: We have 4 colors and 2 posts.Ways when both posts have same color: 4 Ways whe
      15 min read

    • Longest Common Subsequence (LCS)
      Given two strings, s1 and s2, the task is to find the length of the Longest Common Subsequence. If there is no common subsequence, return 0. A subsequence is a string generated from the original string by deleting 0 or more characters, without changing the relative order of the remaining characters.
      15+ min read

    • Longest Increasing Subsequence (LIS)
      Given an array arr[] of size n, the task is to find the length of the Longest Increasing Subsequence (LIS) i.e., the longest possible subsequence in which the elements of the subsequence are sorted in increasing order. Examples: Input: arr[] = [3, 10, 2, 1, 20]Output: 3Explanation: The longest incre
      14 min read

    • Longest subsequence such that difference between adjacents is one
      Given an array arr[] of size n, the task is to find the longest subsequence such that the absolute difference between adjacent elements is 1. Examples: Input: arr[] = [10, 9, 4, 5, 4, 8, 6]Output: 3Explanation: The three possible subsequences of length 3 are [10, 9, 8], [4, 5, 4], and [4, 5, 6], whe
      15+ min read

    • Maximum size square sub-matrix with all 1s
      Given a binary matrix mat of size n * m, the task is to find out the maximum length of a side of a square sub-matrix with all 1s. Example: Input: mat = [ [0, 1, 1, 0, 1], [1, 1, 0, 1, 0], [0, 1, 1, 1, 0], [1, 1, 1, 1, 0], [1, 1, 1, 1, 1], [0, 0, 0, 0, 0] ] Output: 3Explanation: The maximum length of
      15+ min read

    • Min Cost Path
      You are given a 2D matrix cost[][] of dimensions m × n, where each cell represents the cost of traversing through that position. Your goal is to determine the minimum cost required to reach the bottom-right cell (m-1, n-1) starting from the top-left cell (0,0).The total cost of a path is the sum of
      15+ min read

    • Longest Common Substring (Space optimized DP solution)
      Given two strings ‘s1‘ and ‘s2‘, find the length of the longest common substring. Example: Input: s1 = “GeeksforGeeks”, s2 = “GeeksQuiz” Output : 5 Explanation:The longest common substring is “Geeks” and is of length 5. Input: s1 = “abcdxyz”, s2 = “xyzabcd” Output : 4Explanation:The longest common s
      7 min read

    • Count ways to reach the nth stair using step 1, 2 or 3
      A child is running up a staircase with n steps and can hop either 1 step, 2 steps, or 3 steps at a time. The task is to implement a method to count how many possible ways the child can run up the stairs. Examples: Input: 4Output: 7Explanation: There are seven ways: {1, 1, 1, 1}, {1, 2, 1}, {2, 1, 1}
      15+ min read

    • Grid Unique Paths - Count Paths in matrix
      Given an matrix of size m x n, the task is to find the count of all unique possible paths from top left to the bottom right with the constraints that from each cell we can either move only to the right or down. Examples: Input: m = 2, n = 2Output: 2Explanation: There are two paths(0, 0) -> (0, 1)
      15+ min read

    • Unique paths in a Grid with Obstacles
      Given a grid[][] of size m * n, let us assume we are starting at (1, 1) and our goal is to reach (m, n). At any instance, if we are on (x, y), we can either go to (x, y + 1) or (x + 1, y). The task is to find the number of unique paths if some obstacles are added to the grid.Note: An obstacle and sp
      15+ min read

    Medium problems on Dynamic programming

    • 0/1 Knapsack Problem
      Given n items where each item has some weight and profit associated with it and also given a bag with capacity W, [i.e., the bag can hold at most W weight in it]. The task is to put the items into the bag such that the sum of profits associated with them is the maximum possible. Note: The constraint
      15+ min read

    • Printing Items in 0/1 Knapsack
      Given weights and values of n items, put these items in a knapsack of capacity W to get the maximum total value in the knapsack. In other words, given two integer arrays, val[0..n-1] and wt[0..n-1] represent values and weights associated with n items respectively. Also given an integer W which repre
      12 min read

    • Unbounded Knapsack (Repetition of items allowed)
      Given a knapsack weight, say capacity and a set of n items with certain value vali and weight wti, The task is to fill the knapsack in such a way that we can get the maximum profit. This is different from the classical Knapsack problem, here we are allowed to use an unlimited number of instances of
      15+ min read

    • Egg Dropping Puzzle | DP-11
      You are given n identical eggs and you have access to a k-floored building from 1 to k. There exists a floor f where 0 <= f <= k such that any egg dropped from a floor higher than f will break, and any egg dropped from or below floor f will not break. There are a few rules given below: An egg
      15+ min read

    • Word Break
      Given a string s and y a dictionary of n words dictionary, check if s can be segmented into a sequence of valid words from the dictionary, separated by spaces. Examples: Input: s = "ilike", dictionary[] = ["i", "like", "gfg"]Output: trueExplanation: The string can be segmented as "i like". Input: s
      12 min read

    • Vertex Cover Problem (Dynamic Programming Solution for Tree)
      A vertex cover of an undirected graph is a subset of its vertices such that for every edge (u, v) of the graph, either ‘u’ or ‘v’ is in vertex cover. Although the name is Vertex Cover, the set covers all edges of the given graph. The problem to find minimum size vertex cover of a graph is NP complet
      15+ min read

    • Tile Stacking Problem
      Given integers n (the height of the tower), m (the maximum size of tiles available), and k (the maximum number of times each tile size can be used), the task is to calculate the number of distinct stable towers of height n that can be built. Note: A stable tower consists of exactly n tiles, each sta
      15+ min read

    • Box Stacking Problem
      Given three arrays height[], width[], and length[] of size n, where height[i], width[i], and length[i] represent the dimensions of a box. The task is to create a stack of boxes that is as tall as possible, but we can only stack a box on top of another box if the dimensions of the 2-D base of the low
      15+ min read

    • Partition a Set into Two Subsets of Equal Sum
      Given an array arr[], the task is to check if it can be partitioned into two parts such that the sum of elements in both parts is the same.Note: Each element is present in either the first subset or the second subset, but not in both. Examples: Input: arr[] = [1, 5, 11, 5]Output: true Explanation: T
      15+ min read

    • Travelling Salesman Problem using Dynamic Programming
      Given a 2d matrix cost[][] of size n where cost[i][j] denotes the cost of moving from city i to city j. The task is to complete a tour from city 0 (0-based index) to all other cities such that we visit each city exactly once and then at the end come back to city 0 at minimum cost. Note the differenc
      15 min read

    • Longest Palindromic Subsequence (LPS)
      Given a string s, find the length of the Longest Palindromic Subsequence in it. Note: The Longest Palindromic Subsequence (LPS) is the maximum-length subsequence of a given string that is also a Palindrome. Examples: Input: s = "bbabcbcab"Output: 7Explanation: Subsequence "babcbab" is the longest su
      15+ min read

    • Longest Common Increasing Subsequence (LCS + LIS)
      Given two arrays, a[] and b[], find the length of the longest common increasing subsequence(LCIS). LCIS refers to a subsequence that is present in both arrays and strictly increases.Prerequisites: LCS, LIS. Examples: Input: a[] = [3, 4, 9, 1], b[] = [5, 3, 8, 9, 10, 2, 1]Output: 2Explanation: The lo
      15+ min read

    • Find all distinct subset (or subsequence) sums of an array
      Given an array arr[] of size n, the task is to find a distinct sum that can be generated from the subsets of the given sets and return them in increasing order. It is given that the sum of array elements is small. Examples: Input: arr[] = [1, 2]Output: [0, 1, 2, 3]Explanation: Four distinct sums can
      15+ min read

    • Weighted Job Scheduling
      Given a 2D array jobs[][] of order n*3, where each element jobs[i] defines start time, end time, and the profit associated with the job. The task is to find the maximum profit you can take such that there are no two jobs with overlapping time ranges. Note: If the job ends at time X, it is allowed to
      15+ min read

    • Count Derangements (Permutation such that no element appears in its original position)
      A Derangement is a permutation of n elements, such that no element appears in its original position. For example, a derangement of [0, 1, 2, 3] is [2, 3, 1, 0].Given a number n, find the total number of Derangements of a set of n elements. Examples : Input: n = 2Output: 1Explanation: For two balls [
      12 min read

    • Minimum insertions to form a palindrome
      Given a string s, the task is to find the minimum number of characters to be inserted to convert it to a palindrome. Examples: Input: s = "geeks"Output: 3Explanation: "skgeegks" is a palindromic string, which requires 3 insertions. Input: s= "abcd"Output: 3Explanation: "abcdcba" is a palindromic str
      15+ min read

    • Ways to arrange Balls such that adjacent balls are of different types
      There are 'p' balls of type P, 'q' balls of type Q and 'r' balls of type R. Using the balls we want to create a straight line such that no two balls of the same type are adjacent.Examples : Input: p = 1, q = 1, r = 0Output: 2Explanation: There are only two arrangements PQ and QP Input: p = 1, q = 1,
      15+ min read

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