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Hey! I'm Sachin Mishra ,a web and software developer doing my bacheler's in computer science engineering and this website is about Coding and Education facts . I believe Quality is better than quantity


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Sorting Techniques : Selection Sort , Bubble Sort , Insertion Sort

Sorting Techniques 1. Selection Sort: Idea: The inner loop selects the minimum element in the unsorted array  and places the elements in increasing order. Time complexity: O(N 2 ) #include <iostream> using namespace std; int main() {     int n;     cin>>n;   int arr[n];    for(int i=0;i<n;i++){          cin>>arr[i];   }  for(int i=0;i<n-1;i++){       for(int j=i+1;j<n;j++){            if(arr[j]<arr[i]){                 int temp =arr[j];                  arr[j]=arr[i];             arr[i]=temp;           }           }      }for(int i=0;i<n;i++){       cout<<arr[i]<<" ";    }   return 0; } 2. Bubble Sort: Idea: ...

Time and Space complexity : What does time and space complexity mean?

 Time and Space complexity                                  Time Complexity Time complexity of an algorithm quantifies the amount of time taken by an algorithm to run as a function of the length of the input. Types of notations 1. O-notation: It is used to denote asymptotic upper bound. For a given function g(n), we denote it by O(g(n)). Pronounced as “big-oh of g of n”. It also known as worst case time complexity as it denotes the upper bound in which algorithm terminates. 2. Ω-notation: It is used to denote asymptotic lower bound. For a given function g(n), we denote it by Ω(g(n)). Pronounced as “big-omega of g of n”. It also known as best case time complexity as it denotes the lower bound in which algorithm terminates. 3. !-notation: It is used to denote the average time of a program. Comparison of functions on the basis of time complexity It follows the following order in case of time complexit...