Time complexity for my solution to all permutations of integer array containing distinct numbers












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What's the time complexity of my code? I ran this through www.leetcode.com and it's optimal. I think its O(n*n!). First I thought it was O(n^2*n!) : The extra n since we make n recursive calls. However, only the first call to permute() is dominant, and kind of dwarfs the rest since n! is >>> (n-1)!



Thanks upfront!



class Solution {
public List<List<Integer>> permute(int nums) {
return permute(nums, nums.length - 1);
}

private List<List<Integer>> permute(int nums, int n) {
List<List<Integer>> result = new ArrayList<List<Integer>>();
if(n < 0) {
List<Integer> permutation = new ArrayList<Integer>();
result.add(permutation);
return result;
}

// below returns (n-1)! results of size n-1 each
List<List<Integer>> prefixes = permute(nums, n-1);
for(List<Integer> prefix : prefixes) {
List<List<Integer>> permutations = insert(nums[n], prefix);
result.addAll(permutations);
}
return result;
}

// O(n^2) worst case when size of list is n-1
private List<List<Integer>> insert(int num, List<Integer> list) {
List<List<Integer>> result = new ArrayList<List<Integer>>();
for(int i = 0; i <= list.size(); i++) {
List<Integer> clone = new ArrayList<Integer>();
clone.addAll(list);
clone.add(i, num);
result.add(clone);
}
return result;
}

}








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    $begingroup$


    What's the time complexity of my code? I ran this through www.leetcode.com and it's optimal. I think its O(n*n!). First I thought it was O(n^2*n!) : The extra n since we make n recursive calls. However, only the first call to permute() is dominant, and kind of dwarfs the rest since n! is >>> (n-1)!



    Thanks upfront!



    class Solution {
    public List<List<Integer>> permute(int nums) {
    return permute(nums, nums.length - 1);
    }

    private List<List<Integer>> permute(int nums, int n) {
    List<List<Integer>> result = new ArrayList<List<Integer>>();
    if(n < 0) {
    List<Integer> permutation = new ArrayList<Integer>();
    result.add(permutation);
    return result;
    }

    // below returns (n-1)! results of size n-1 each
    List<List<Integer>> prefixes = permute(nums, n-1);
    for(List<Integer> prefix : prefixes) {
    List<List<Integer>> permutations = insert(nums[n], prefix);
    result.addAll(permutations);
    }
    return result;
    }

    // O(n^2) worst case when size of list is n-1
    private List<List<Integer>> insert(int num, List<Integer> list) {
    List<List<Integer>> result = new ArrayList<List<Integer>>();
    for(int i = 0; i <= list.size(); i++) {
    List<Integer> clone = new ArrayList<Integer>();
    clone.addAll(list);
    clone.add(i, num);
    result.add(clone);
    }
    return result;
    }

    }








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      $begingroup$


      What's the time complexity of my code? I ran this through www.leetcode.com and it's optimal. I think its O(n*n!). First I thought it was O(n^2*n!) : The extra n since we make n recursive calls. However, only the first call to permute() is dominant, and kind of dwarfs the rest since n! is >>> (n-1)!



      Thanks upfront!



      class Solution {
      public List<List<Integer>> permute(int nums) {
      return permute(nums, nums.length - 1);
      }

      private List<List<Integer>> permute(int nums, int n) {
      List<List<Integer>> result = new ArrayList<List<Integer>>();
      if(n < 0) {
      List<Integer> permutation = new ArrayList<Integer>();
      result.add(permutation);
      return result;
      }

      // below returns (n-1)! results of size n-1 each
      List<List<Integer>> prefixes = permute(nums, n-1);
      for(List<Integer> prefix : prefixes) {
      List<List<Integer>> permutations = insert(nums[n], prefix);
      result.addAll(permutations);
      }
      return result;
      }

      // O(n^2) worst case when size of list is n-1
      private List<List<Integer>> insert(int num, List<Integer> list) {
      List<List<Integer>> result = new ArrayList<List<Integer>>();
      for(int i = 0; i <= list.size(); i++) {
      List<Integer> clone = new ArrayList<Integer>();
      clone.addAll(list);
      clone.add(i, num);
      result.add(clone);
      }
      return result;
      }

      }








      share







      New contributor




      Aran is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.







      $endgroup$




      What's the time complexity of my code? I ran this through www.leetcode.com and it's optimal. I think its O(n*n!). First I thought it was O(n^2*n!) : The extra n since we make n recursive calls. However, only the first call to permute() is dominant, and kind of dwarfs the rest since n! is >>> (n-1)!



      Thanks upfront!



      class Solution {
      public List<List<Integer>> permute(int nums) {
      return permute(nums, nums.length - 1);
      }

      private List<List<Integer>> permute(int nums, int n) {
      List<List<Integer>> result = new ArrayList<List<Integer>>();
      if(n < 0) {
      List<Integer> permutation = new ArrayList<Integer>();
      result.add(permutation);
      return result;
      }

      // below returns (n-1)! results of size n-1 each
      List<List<Integer>> prefixes = permute(nums, n-1);
      for(List<Integer> prefix : prefixes) {
      List<List<Integer>> permutations = insert(nums[n], prefix);
      result.addAll(permutations);
      }
      return result;
      }

      // O(n^2) worst case when size of list is n-1
      private List<List<Integer>> insert(int num, List<Integer> list) {
      List<List<Integer>> result = new ArrayList<List<Integer>>();
      for(int i = 0; i <= list.size(); i++) {
      List<Integer> clone = new ArrayList<Integer>();
      clone.addAll(list);
      clone.add(i, num);
      result.add(clone);
      }
      return result;
      }

      }






      java algorithm array recursion combinatorics





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