Givet to strenge s1 og s2 . Opgaven er at fjerne/slette og indsætte de minimum antal tegn fra s1 at forvandle det til s2 . Det kunne være muligt, at samme karakter skal fjernes/slettes fra ét punkt af s1 og indsat på et andet sted.
Eksempel 1:
Input: s1 = 'dynge' s2 =
Produktion: 3
Forklaring: Minimum sletning = 2 og minimumsindsættelse = 1
p og h slettes fra heapen, og derefter indsættes p i begyndelsen. En ting at bemærke, selvom p var påkrævet, blev den fjernet/slettet først fra sin position, og derefter blev den indsat i en anden position. Således bidrager p én til deletionstællingen og én til insertionstællingen.Input: s1 = 'geeksforgeeks' s2 = 'geeks'
Produktion: 8
Forklaring: 8 sletninger, dvs. fjern alle tegn i strengen 'forgeeks'.
Indholdsfortegnelse
- Brug af rekursion - O(2^n) Tid og O(n) Mellemrum
- Brug af Top-Down DP (Memoization) - O(n^2) Tid og O(n^2) Rum
- Brug af Bottom-Up DP (Tabulering) - O(n^2) Tid og O(n^2) Rum
- Brug af Bottom-Up DP (Space-Optimization) – O(n^2) Tid og O(n) Space
Brug af rekursion - O(2^n) Tid og O(n) Mellemrum
C++En simpel tilgang til at løse problemet involverer at generere alle efterfølger af s1 og for hver efterfølgende beregning af minimum sletninger og indsættelser, der kræves for at transformere den til s2. En effektiv tilgang bruger begrebet længste fælles subsequence (LCS) at finde længden af længste LCS. Når vi har LCS af to strenge, kan vi finde Minimum indsættelse og Sletninger at konvertere s1 til s2.
- Til minimere sletninger vi behøver kun at fjerne tegn fra s1 som ikke er en del af længste fælles subsequence (LCS) med s2 . Dette kan bestemmes ved trække fra de LCS længde fra længden af s1 . Minimumsantallet af sletninger er således:
minDeletions = længden af s1 - LCS længde.- Ligesom minimere indsættelser vi skal kun indsætte tegn fra s2 til s1 som ikke er en del af LCS. Dette kan bestemmes ved trække fra de LCS længde fra længden af s2 . Minimumsantallet af indsættelser er således:
minInsertions = længden af s2 - LCS længde.
// 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
Brug af Top-Down DP (Memoization) - O(n^2) Tid og O(n^2) Rum
C++I denne tilgang anvender vi huskes at gemme resultaterne af overlappende underproblemer, mens man finder den længste fælles undersekvens (LCS). EN 2D-array notat bruges til at gemme LCS længder for forskellige understrenge af de to inputstrenge, hvilket sikrer, at hvert underproblem kun løses én gang.
Denne metode ligner Længste fælles efterfølger (LCS) problem med at bruge huskeseddel.
// 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
Brug af Bottom-Up DP (Tabulering) - O(n^2) Tid og O(n^2) Rum
C++Fremgangsmåden ligner forrige bare i stedet for at nedbryde problemet rekursivt vi iterativt opbygge løsningen ved at regne ind nedefra og op måde. Vi opretholder en 2D dp[][] tabel sådan at dp[i][j] gemmer Længste fælles efterfølger (LCS) for underproblem (i j) .
Denne tilgang ligner at finde LCS på bottom-up måde .
// 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
Brug af Bottom-Up DP (Space-Optimization) – O(n^2) Tid og O(n) Space
C++I den tidligere tilgang længste fælles subsequence (LCS) algoritme bruger O(n * n) plads til at opbevare det hele dp tabel . Men da hver værdi i dp[i][j ] afhænger kun af nuværende række og den forrige række vi behøver ikke opbevare hele bordet. Dette kan optimeres ved kun at gemme den nuværende og tidligere rækker. For flere detaljer henvises til En rumoptimeret løsning af 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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