Givet två strängar s1 och s2 . Uppgiften är att ta bort/ta bort och infoga de minsta antal tecken från s1 att förvandla det till s2 . Det kan vara möjligt att samma karaktär måste tas bort/raderas från en punkt av s1 och infogas vid en annan punkt.
Exempel 1:
Input: s1 = 'hög' s2 =
Produktion: 3
Förklaring: Minsta radering = 2 och Minsta insättning = 1
p och h raderas från högen och sedan infogas p i början. En sak att notera även om p krävdes togs den bort/raderades först från sin position och sedan infogades den i någon annan position. Således bidrar p en till raderingsräkningen och en till insättningsräkningen.Input: s1 = 'nördar' s2 = 'nördar'
Produktion: 8
Förklaring: 8 raderingar, dvs ta bort alla tecken i strängen "forgeeks".
Innehållsförteckning
- Använda Rekursion - O(2^n) Tid och O(n) Mellanrum
- Använda Top-Down DP (Memoization) - O(n^2) Tid och O(n^2) Space
- Använda Bottom-Up DP (Tabulering) - O(n^2) Tid och O(n^2) Space
- Använda Bottom-Up DP (Space-Optimization) – O(n^2) Tid och O(n) Space
Använda Rekursion - O(2^n) Tid och O(n) Mellanrum
C++Ett enkelt sätt att lösa problemet innebär att generera alla följder av s1 och för varje efterföljande beräkning av minimum raderingar och infogningar som krävs för att omvandla den till s2. Ett effektivt tillvägagångssätt använder begreppet längsta vanliga följdsekvensen (LCS) för att hitta längden på längsta LCS. När vi väl har LCS av två strängar kan vi hitta Minsta insättning och Borttagningar att konvertera s1 till s2.
- Till minimera raderingar vi behöver bara ta bort tecken från s1 som inte är en del av längsta vanliga följdsekvensen (LCS) med s2 . Detta kan bestämmas av subtrahera de LCS längd från längden av s1 . Så det minsta antalet raderingar är:
minDeletions = längd av s1 - LCS längd.- Likadant till minimera insättningar vi behöver bara infoga tecken från s2 till s1 som inte är en del av LCS. Detta kan bestämmas av subtrahera de LCS längd från längden av s2 . Det minsta antalet infogningar är alltså:
minInsertions = längd av s2 – LCS längd.
// C++ program to find the minimum number of insertion and deletion // using recursion. #include
// Java program to find the minimum number of insertions and // deletions using recursion. class GfG { static int lcs(String s1 String s2 int m int n) { // Base case: If either string is empty the LCS // length is 0 if (m == 0 || n == 0) { return 0; } // If the last characters of both substrings match if (s1.charAt(m - 1) == s2.charAt(n - 1)) { // Include the matching character in LCS // and recurse for remaining substrings return 1 + lcs(s1 s2 m - 1 n - 1); } else { // If the last characters do not match // find the maximum LCS length by: // 1. Excluding the last character of s1 // 2. Excluding the last character of s2 return Math.max(lcs(s1 s2 m n - 1) lcs(s1 s2 m - 1 n)); } } static int minOperations(String s1 String s2) { int m = s1.length(); int n = s2.length(); // the length of LCS for s1[0..m-1] and // s2[0..n-1] int len = lcs(s1 s2 m n); // Characters to delete from s1 int minDeletions = m - len; // Characters to insert into s2 int minInsertions = n - len; // Total operations needed return minDeletions + minInsertions; } public static void main(String[] args) { String s1 = 'AGGTAB'; String s2 = 'GXTXAYB'; int res = minOperations(s1 s2); System.out.println(res); } }
# Python program to find the minimum number of insertions # and deletions using recursion def lcs(s1 s2 m n): # Base case: If either string is empty # the LCS length is 0 if m == 0 or n == 0: return 0 # If the last characters of both substrings match if s1[m - 1] == s2[n - 1]: # Include the matching character in LCS and # recurse for remaining substrings return 1 + lcs(s1 s2 m - 1 n - 1) else: # If the last characters do not match # find the maximum LCS length by: # 1. Excluding the last character of s1 # 2. Excluding the last character of s2 return max(lcs(s1 s2 m n - 1) lcs(s1 s2 m - 1 n)) def minOperations(s1 s2): m = len(s1) n = len(s2) # the length of LCS for s1[0..m-1] and s2[0..n-1] lengthLcs = lcs(s1 s2 m n) # Characters to delete from str1 minDeletions = m - lengthLcs # Characters to insert into str1 minInsertions = n - lengthLcs # Total operations needed return minDeletions + minInsertions if __name__ == '__main__': s1 = 'AGGTAB' s2 = 'GXTXAYB' result = minOperations(s1 s2) print(result)
// C# program to find the minimum number of insertions and // deletions using recursion. using System; class GfG { static int lcs(string s1 string s2 int m int n) { // Base case: If either string is empty the LCS // length is 0 if (m == 0 || n == 0) return 0; // If the last characters of both substrings match if (s1[m - 1] == s2[n - 1]) { // Include the matching character in LCS // and recurse for remaining substrings return 1 + lcs(s1 s2 m - 1 n - 1); } else { // If the last characters do not match // find the maximum LCS length by: // 1. Excluding the last character of s1 // 2. Excluding the last character of s2 return Math.Max(lcs(s1 s2 m n - 1) lcs(s1 s2 m - 1 n)); } } static int minOperations(string s1 string s2) { int m = s1.Length; int n = s2.Length; // the length of LCS for s1[0..m-1] and // s2[0..n-1] int lengthLcs = lcs(s1 s2 m n); // Characters to delete from s1 int minDeletions = m - lengthLcs; // Characters to insert into s2 int minInsertions = n - lengthLcs; // Total operations needed return minDeletions + minInsertions; } static void Main(string[] args) { string s1 = 'AGGTAB'; string s2 = 'GXTXAYB'; int result = minOperations(s1 s2); Console.WriteLine(result); } }
// JavaScript program to find the minimum number of // insertions and deletions using recursion function lcs(s1 s2 m n) { // Base case: If either string is empty the LCS length // is 0 if (m === 0 || n === 0) { return 0; } // If the last characters of both substrings match if (s1[m - 1] === s2[n - 1]) { // Include the matching character in LCS and recurse // for remaining substrings return 1 + lcs(s1 s2 m - 1 n - 1); } else { // If the last characters do not match find the // maximum LCS length by: // 1. Excluding the last character of s1 // 2. Excluding the last character of s2 return Math.max(lcs(s1 s2 m n - 1) lcs(s1 s2 m - 1 n)); } } function minOperations(s1 s2) { const m = s1.length; const n = s2.length; // Length of the LCS const len = lcs(s1 s2 m n); // Characters to delete from s1 const minDeletions = m - len; // Characters to insert into s1 const minInsertions = n - len; // Total operations needed return minDeletions + minInsertions; } const s1 = 'AGGTAB'; const s2 = 'GXTXAYB'; const res = minOperations(s1 s2); console.log(res);
Produktion
5
Använda Top-Down DP (Memoization) - O(n^2) Tid och O(n^2) Space
C++I detta tillvägagångssätt tillämpar vi memoisering för att lagra resultaten av överlappande delproblem samtidigt som man hittar den längsta gemensamma subsekvensen (LCS). A 2D-array pm används för att spara LCS längder för olika delsträngar av de två inmatningssträngarna, vilket säkerställer att varje delproblem endast löses en gång.
Denna metod liknar Longest Common Subsequence (LCS) problem med att använda memoisering.
// C++ program to find the minimum of insertion and deletion // using memoization. #include
// Java program to find the minimum of insertion and deletion // using memoization. class GfG { static int lcs(String s1 String s2 int m int n int[][] memo) { // Base case: If either string is empty // the LCS length is 0 if (m == 0 || n == 0) { return 0; } // If the value is already computed return it // from the memo array if (memo[m][n] != -1) { return memo[m][n]; } // If the last characters of both substrings match if (s1.charAt(m - 1) == s2.charAt(n - 1)) { // Include the matching character in LCS and recurse for // remaining substrings memo[m][n] = 1 + lcs(s1 s2 m - 1 n - 1 memo); } else { // If the last characters do not match // find the maximum LCS length by: // 1. Excluding the last character of s1 // 2. Excluding the last character of s2 memo[m][n] = Math.max(lcs(s1 s2 m n - 1 memo) lcs(s1 s2 m - 1 n memo)); } return memo[m][n]; } static int minOperations(String s1 String s2) { int m = s1.length(); int n = s2.length(); // Initialize the memoization array with -1 // (indicating uncalculated values) int[][] memo = new int[m + 1][n + 1]; for (int i = 0; i <= m; i++) { for (int j = 0; j <= n; j++) { memo[i][j] = -1; } } // the length of LCS for s1[0..m-1] and s2[0..n-1] int len = lcs(s1 s2 m n memo); // Characters to delete from s1 int minDeletions = m - len; // Characters to insert into s1 int minInsertions = n - len; // Total operations needed return minDeletions + minInsertions; } static void main(String[] args) { String s1 = 'AGGTAB'; String s2 = 'GXTXAYB'; int res = minOperations(s1 s2); System.out.println(res); } }
# Python program to find the minimum number of insertions and # deletions using memoization def lcs(s1 s2 m n memo): # Base case: If either string is empty the LCS length is 0 if m == 0 or n == 0: return 0 # If the value is already computed # return it from the memo array if memo[m][n] != -1: return memo[m][n] # If the last characters of both substrings match if s1[m - 1] == s2[n - 1]: # Include the matching character in LCS and # recurse for remaining substrings memo[m][n] = 1 + lcs(s1 s2 m - 1 n - 1 memo) else: # If the last characters do not match # find the maximum LCS length by: # 1. Excluding the last character of s1 # 2. Excluding the last character of s2 memo[m][n] = max(lcs(s1 s2 m n - 1 memo) lcs(s1 s2 m - 1 n memo)) # Return the computed value return memo[m][n] def minOperations(s1 s2): m = len(s1) n = len(s2) # Initialize the memoization array with -1 # (indicating uncalculated values) memo = [[-1 for _ in range(n + 1)] for _ in range(m + 1)] # Calculate the length of LCS for s1[0..m-1] and s2[0..n-1] lengthLcs = lcs(s1 s2 m n memo) # Characters to delete from s1 minDeletions = m - lengthLcs # Characters to insert into s1 minInsertions = n - lengthLcs # Total operations needed return minDeletions + minInsertions if __name__ == '__main__': s1 = 'AGGTAB' s2 = 'GXTXAYB' res = minOperations(s1 s2) print(res)
// C# program to find the minimum of insertion and deletion // using memoization. using System; class GfG { static int lcs(string s1 string s2 int m int n int[ ] memo) { // Base case: If either string is empty the LCS // length is 0 if (m == 0 || n == 0) { return 0; } // If the value is already computed return it from // the memo array if (memo[m n] != -1) { return memo[m n]; } // If the last characters of both substrings match if (s1[m - 1] == s2[n - 1]) { // Include the matching character in LCS and // recurse for remaining substrings memo[m n] = 1 + lcs(s1 s2 m - 1 n - 1 memo); } else { // If the last characters do not match find the // maximum LCS length by: // 1. Excluding the last character of s1 // 2. Excluding the last character of s2 memo[m n] = Math.Max(lcs(s1 s2 m n - 1 memo) lcs(s1 s2 m - 1 n memo)); } // Return the computed value return memo[m n]; } static int minOperations(string s1 string s2) { int m = s1.Length; int n = s2.Length; // Initialize the memoization array with -1 // (indicating uncalculated values) int[ ] memo = new int[m + 1 n + 1]; for (int i = 0; i <= m; i++) { for (int j = 0; j <= n; j++) { memo[i j] = -1; } } // Calculate the length of LCS for s1[0..m-1] and // s2[0..n-1] int lengthLcs = lcs(s1 s2 m n memo); // Characters to delete from s1 int minDeletions = m - lengthLcs; // Characters to insert into s1 int minInsertions = n - lengthLcs; // Total operations needed return minDeletions + minInsertions; } static void Main(string[] args) { string s1 = 'AGGTAB'; string s2 = 'GXTXAYB'; int res = minOperations(s1 s2); Console.WriteLine(res); } }
// JavaScript program to find the minimum number of // insertions and deletions using memoization function lcs(s1 s2 m n memo) { // Base case: If either string is empty the LCS length // is 0 if (m === 0 || n === 0) { return 0; } // If the value is already computed return it from the // memo array if (memo[m][n] !== -1) { return memo[m][n]; } // If the last characters of both substrings match if (s1[m - 1] === s2[n - 1]) { // Include the matching character in LCS and recurse // for remaining substrings memo[m][n] = 1 + lcs(s1 s2 m - 1 n - 1 memo); } else { // If the last characters do not match find the // maximum LCS length by: // 1. Excluding the last character of s1 // 2. Excluding the last character of s2 memo[m][n] = Math.max(lcs(s1 s2 m n - 1 memo) lcs(s1 s2 m - 1 n memo)); } return memo[m][n]; } function minOperations(s1 s2){ const m = s1.length; const n = s2.length; // Initialize the memoization array with -1 (indicating // uncalculated values) const memo = Array.from({length : m + 1} () => Array(n + 1).fill(-1)); // Calculate the length of LCS for s1[0..m-1] and // s2[0..n-1] const len = lcs(s1 s2 m n memo); // Characters to delete from s1 const minDeletions = m - len; // Characters to insert into s1 const minInsertions = n - len; // Total operations needed return minDeletions + minInsertions; } const s1 = 'AGGTAB'; const s2 = 'GXTXAYB'; const res = minOperations(s1 s2); console.log(res);
Produktion
5
Använda Bottom-Up DP (Tabulering) - O(n^2) Tid och O(n^2) Space
C++Tillvägagångssättet liknar föregående bara istället för att bryta ner problemet rekursivt vi iterativt bygga upp lösningen genom att räkna in nedifrån och upp sätt. Vi upprätthåller en 2D dp[][] tabell så att dp[i][j] lagrar Longest Common Subsequence (LCS) för delproblem (i j) .
Detta tillvägagångssätt liknar att hitta LCS på ett bottom-up sätt .
// C++ program to find the minimum of insertion and deletion // using tabulation. #include
// Java program to find the minimum of insertion and // deletion using tabulation. class GfG { static int lcs(String s1 String s2) { int m = s1.length(); int n = s2.length(); // Initializing a matrix of size (m+1)*(n+1) int[][] dp = new int[m + 1][n + 1]; // Building dp[m+1][n+1] in bottom-up fashion for (int i = 1; i <= m; ++i) { for (int j = 1; j <= n; ++j) { if (s1.charAt(i - 1) == s2.charAt(j - 1)) dp[i][j] = dp[i - 1][j - 1] + 1; else dp[i][j] = Math.max(dp[i - 1][j] dp[i][j - 1]); } } // dp[m][n] contains length of LCS for s1[0..m-1] // and s2[0..n-1] return dp[m][n]; } static int minOperations(String s1 String s2) { int m = s1.length(); int n = s2.length(); // the length of the LCS for s1[0..m-1] and // str2[0..n-1] int len = lcs(s1 s2); // Characters to delete from s1 int minDeletions = m - len; // Characters to insert into s1 int minInsertions = n - len; // Total operations needed return minDeletions + minInsertions; } public static void main(String[] args) { String s1 = 'AGGTAB'; String s2 = 'GXTXAYB'; int res = minOperations(s1 s2); System.out.println(res); } }
# Python program to find the minimum of insertion and deletion # using tabulation. def lcs(s1 s2): m = len(s1) n = len(s2) # Initializing a matrix of size (m+1)*(n+1) dp = [[0] * (n + 1) for _ in range(m + 1)] # Building dp[m+1][n+1] in bottom-up fashion for i in range(1 m + 1): for j in range(1 n + 1): if s1[i - 1] == s2[j - 1]: dp[i][j] = dp[i - 1][j - 1] + 1 else: dp[i][j] = max(dp[i - 1][j] dp[i][j - 1]) # dp[m][n] contains length of LCS for # s1[0..m-1] and s2[0..n-1] return dp[m][n] def minOperations(s1 s2): m = len(s1) n = len(s2) # the length of the LCS for # s1[0..m-1] and s2[0..n-1] lengthLcs = lcs(s1 s2) # Characters to delete from s1 minDeletions = m - lengthLcs # Characters to insert into s1 minInsertions = n - lengthLcs # Total operations needed return minDeletions + minInsertions s1 = 'AGGTAB' s2 = 'GXTXAYB' res = minOperations(s1 s2) print(res)
// C# program to find the minimum of insertion and deletion // using tabulation. using System; class GfG { static int Lcs(string s1 string s2) { int m = s1.Length; int n = s2.Length; // Initializing a matrix of size (m+1)*(n+1) int[ ] dp = new int[m + 1 n + 1]; // Building dp[m+1][n+1] in bottom-up fashion for (int i = 1; i <= m; ++i) { for (int j = 1; j <= n; ++j) { if (s1[i - 1] == s2[j - 1]) dp[i j] = dp[i - 1 j - 1] + 1; else dp[i j] = Math.Max(dp[i - 1 j] dp[i j - 1]); } } // dp[m n] contains length of LCS for s1[0..m-1] // and s2[0..n-1] return dp[m n]; } static int minOperations(string s1 string s2) { int m = s1.Length; int n = s2.Length; // the length of the LCS for s1[0..m-1] and // s2[0..n-1] int len = Lcs(s1 s2); // Characters to delete from str1 int minDeletions = m - len; // Characters to insert into str1 int minInsertions = n - len; // Total operations needed return minDeletions + minInsertions; } static void Main() { string s1 = 'AGGTAB'; string s2 = 'GXTXAYB'; int res = minOperations(s1 s2); Console.WriteLine(res); } }
// JavaScript program to find the minimum of insertion and // deletion using tabulation. function lcs(s1 s2) { let m = s1.length; let n = s2.length; // Initializing a matrix of size (m+1)*(n+1) let dp = Array(m + 1).fill().map( () => Array(n + 1).fill(0)); // Building dp[m+1][n+1] in bottom-up fashion for (let i = 1; i <= m; ++i) { for (let j = 1; j <= n; ++j) { if (s1[i - 1] === s2[j - 1]) dp[i][j] = dp[i - 1][j - 1] + 1; else dp[i][j] = Math.max(dp[i - 1][j] dp[i][j - 1]); } } // dp[m][n] contains length of LCS for s1[0..m-1] and // s2[0..n-1] return dp[m][n]; } function minOperations(s1 s2) { let m = s1.length; let n = s2.length; // the length of the LCS for s1[0..m-1] and s2[0..n-1] let len = lcs(s1 s2); // Characters to delete from s1 let minDeletions = m - len; // Characters to insert into s1 let minInsertions = n - len; // Total operations needed return minDeletions + minInsertions; } let s1 = 'AGGTAB'; let s2 = 'GXTXAYB'; let res = minOperations(s1 s2); console.log(res);
Produktion
5
Använda Bottom-Up DP (Space-Optimization) – O(n^2) Tid och O(n) Space
C++I det tidigare tillvägagångssättet längsta vanliga följdsekvensen (LCS) algoritmen använder O(n * n) utrymme för att förvara hela dp tabell . Men eftersom varje värde i dp[i][j ] beror bara på nuvarande rad och den föregående rad vi behöver inte förvara hela bordet. Detta kan optimeras genom att endast lagra nuvarande och föregående rader. För mer information se En rymdoptimerad lösning av LCS .
// C++ program to find the minimum of insertion and deletion // using space optimized. #include
// Java program to find the minimum of insertion and // deletion using space optimized. class GfG { static int lcs(String s1 String s2) { int m = s1.length(); int n = s2.length(); // Initializing a 2D array with size (2) x (n + 1) int[][] dp = new int[2][n + 1]; for (int i = 0; i <= m; i++) { // Compute current binary index. If i is even // then curr = 0 else 1 int curr = i % 2; for (int j = 0; j <= n; j++) { // Initialize first row and first column // with 0 if (i == 0 || j == 0) dp[curr][j] = 0; else if (s1.charAt(i - 1) == s2.charAt(j - 1)) dp[curr][j] = dp[1 - curr][j - 1] + 1; else dp[curr][j] = Math.max(dp[1 - curr][j] dp[curr][j - 1]); } } return dp[m % 2][n]; } static int minOperations(String s1 String s2) { int m = s1.length(); int n = s2.length(); // the length of the LCS for s1[0..m-1] and // s2[0..n-1] int len = lcs(s1 s2); // Characters to delete from s1 int minDeletions = m - len; // Characters to insert into s1 int minInsertions = n - len; // Total operations needed return minDeletions + minInsertions; } public static void main(String[] args) { String s1 = 'AGGTAB'; String s2 = 'GXTXAYB'; int res = minOperations(s1 s2); System.out.println(res); } }
# Python program to find the minimum of insertion and deletion # using space optimized. def lcs(s1 s2): m = len(s1) n = len(s2) # Initializing a matrix of size (2)*(n+1) dp = [[0] * (n + 1) for _ in range(2)] for i in range(m + 1): # Compute current binary index. If i is even # then curr = 0 else 1 curr = i % 2 for j in range(n + 1): # Initialize first row and first column with 0 if i == 0 or j == 0: dp[curr][j] = 0 # If the last characters of both substrings match elif s1[i - 1] == s2[j - 1]: dp[curr][j] = dp[1 - curr][j - 1] + 1 # If the last characters do not match # find the maximum LCS length by: # 1. Excluding the last character of s1 # 2. Excluding the last character of s2 else: dp[curr][j] = max(dp[1 - curr][j] dp[curr][j - 1]) # dp[m & 1][n] contains length of LCS for s1[0..m-1] and s2[0..n-1] return dp[m % 2][n] def minOperations(s1 s2): m = len(s1) n = len(s2) # the length of the LCS for s1[0..m-1] and s2[0..n-1] length = lcs(s1 s2) # Characters to delete from s1 minDeletions = m - length # Characters to insert into s1 minInsertions = n - length # Total operations needed return minDeletions + minInsertions s1 = 'AGGTAB' s2 = 'GXTXAYB' res = minOperations(s1 s2) print(res)
// C# program to find the minimum of insertion and deletion // using space optimized. using System; class GfG { static int lcs(string s1 string s2) { int m = s1.Length; int n = s2.Length; // Initializing a matrix of size (2)*(n+1) int[][] dp = new int[2][]; dp[0] = new int[n + 1]; dp[1] = new int[n + 1]; for (int i = 0; i <= m; i++) { // Compute current binary index. If i is even // then curr = 0 else 1 int curr = i % 2; for (int j = 0; j <= n; j++) { // Initialize first row and first column // with 0 if (i == 0 || j == 0) dp[curr][j] = 0; // If the last characters of both substrings // match else if (s1[i - 1] == s2[j - 1]) dp[curr][j] = dp[1 - curr][j - 1] + 1; // If the last characters do not match // find the maximum LCS length by: // 1. Excluding the last character of s1 // 2. Excluding the last character of s2 else dp[curr][j] = Math.Max(dp[1 - curr][j] dp[curr][j - 1]); } } // dp[m & 1][n] contains length of LCS for // s1[0..m-1] and s2[0..n-1] return dp[m % 2][n]; } static int minOperations(string s1 string s2) { int m = s1.Length; int n = s2.Length; // the length of the LCS for s1[0..m-1] and // s2[0..n-1] int length = lcs(s1 s2); // Characters to delete from s1 int minDeletions = m - length; // Characters to insert into s1 int minInsertions = n - length; // Total operations needed return minDeletions + minInsertions; } static void Main(string[] args) { string s1 = 'AGGTAB'; string s2 = 'GXTXAYB'; int res = minOperations(s1 s2); Console.WriteLine(res); } }
// JavaScript program to find the minimum of insertion and // deletion using space optimized. function lcs(s1 s2) { const m = s1.length; const n = s2.length; // Initializing a matrix of size (2)*(n+1) const dp = Array(2).fill().map(() => Array(n + 1).fill(0)); for (let i = 0; i <= m; i++) { // Compute current binary index. If i is even // then curr = 0 else 1 const curr = i % 2; for (let j = 0; j <= n; j++) { // Initialize first row and first column with 0 if (i === 0 || j === 0) dp[curr][j] = 0; // If the last characters of both substrings // match else if (s1[i - 1] === s2[j - 1]) dp[curr][j] = dp[1 - curr][j - 1] + 1; // If the last characters do not match // find the maximum LCS length by: // 1. Excluding the last character of s1 // 2. Excluding the last character of s2 else dp[curr][j] = Math.max(dp[1 - curr][j] dp[curr][j - 1]); } } // dp[m & 1][n] contains length of LCS for s1[0..m-1] // and s2[0..n-1] return dp[m % 2][n]; } function minOperations(s1 s2) { const m = s1.length; const n = s2.length; // the length of the LCS for s1[0..m-1] and s2[0..n-1] const length = lcs(s1 s2); // Characters to delete from s1 const minDeletions = m - length; // Characters to insert into s1 const minInsertions = n - length; // Total operations needed return minDeletions + minInsertions; } const s1 = 'AGGTAB'; const s2 = 'GXTXAYB'; const res = minOperations(s1 s2); console.log(res);
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