The time complexity for the loop with elementary operations: Assuming these operations take unit time for execution. This unit time can be denoted by O(1). If the loop runs for N times without any comparison. Below is the illustration for the same: // C++ program to illustrate time // complexity for single for-loop #include using namespace std;   // Driver Code int main() {     int a = 0, b = 0;     int N = 4, M = 4;       // This loop runs for N time     for (int i = 0; i < N; i++) {         a = a + 10;     }     // This loop runs for M time     for (int i = 0; i < M; i++) {         b = b + 40;     }       cout << a << ' ' << b;       return 0; } Create an ipo, then analyze it until you get a big O 1. Determine the problem to be solved with a particular algorithm 2. Develop algorithms (in the algorithm there must be at least 1 iteration operation, 1 selection operation and several assignment operations) 3. Algorithm analysis 4. Determine the Big O

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The time complexity for the loop with elementary operations: Assuming these operations take unit time for execution. This unit time can be denoted by O(1). If the loop runs for N times without any comparison. Below is the illustration for the same:

// C++ program to illustrate time
// complexity for single for-loop
#include <bits/stdc++.h>
using namespace std;
 
// Driver Code
int main()
{
    int a = 0, b = 0;
    int N = 4, M = 4;
 
    // This loop runs for N time
    for (int i = 0; i < N; i++) {
        a = a + 10;
    }
    // This loop runs for M time
    for (int i = 0; i < M; i++) {
        b = b + 40;
    }
 
    cout << a << ' ' << b;
 
    return 0;
}

Create an ipo, then analyze it until you get a big O
1. Determine the problem to be solved with a particular algorithm
2. Develop algorithms (in the algorithm there must be at least 1 iteration operation, 1 selection operation and several assignment operations)
3. Algorithm analysis
4. Determine the Big O

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