The time complexity of this function can be determined by analyzing the number of iterations in the nested loops.

1. The outer loop runs from 1 to n, so it has a time complexity of O(n).

2. The inner loop runs from 1 to m, where m is updated in each iteration of the outer loop. The value of m is multiplied by 3 in each iteration of the outer loop. Initially, m is 1, and in the first iteration of the outer loop, m becomes 3. In the second iteration, m becomes 9, and so on.

3. The number of iterations in the inner loop can be calculated as follows:

1 + 3 + 9 + 27 + ... + 3^k

where k is the number of iterations in the outer loop (n).

4. This is a geometric series with a common ratio of 3. The sum of a geometric series can be calculated using the formula:

sum = (a * (r^k - 1)) / (r - 1)

In this case, a = 1, r = 3, and k = n. Plugging in these values, we get:

sum = (1 * (3^n - 1)) / (3 - 1)
= (3^n - 1) / 2

Therefore, the number of iterations in the inner loop is (3^n - 1) / 2.

5. Since the inner loop is nested inside the outer loop, the total number of iterations is the product of the number of iterations in the outer loop and the number of iterations in the inner loop:

Total iterations = O(n) * ((3^n - 1) / 2)
= O(n * (3^n))

Therefore, the time complexity of this function is O(n * (3^n)).

Question

The time complexity of this function can be determined by analyzing the number of iterations in the nested loops.

1. The outer loop runs from 1 to n, so it has a time complexity of O(n).

2. The inner loop runs from 1 to m, where m is updated in each iteration of the outer loop. The value of m is multiplied by 3 in each iteration of the outer loop. Initially, m is 1, and in the first iteration of the outer loop, m becomes 3. In the second iteration, m becomes 9, and so on.

3. The number of iterations in the inner loop can be calculated as follows:

1 + 3 + 9 + 27 + ... + 3^k

where k is the number of iterations in the outer loop (n).

4. This is a geometric series with a common ratio of 3. The sum of a geometric series can be calculated using the formula:

sum = (a * (r^k - 1)) / (r - 1)

In this case, a = 1, r = 3, and k = n. Plugging in these values, we get:

sum = (1 * (3^n - 1)) / (3 - 1)
        = (3^n - 1) / 2

Therefore, the number of iterations in the inner loop is (3^n - 1) / 2.

5. Since the inner loop is nested inside the outer loop, the total number of iterations is the product of the number of iterations in the outer loop and the number of iterations in the inner loop:

Total iterations = O(n) * ((3^n - 1) / 2)
                  = O(n * (3^n))

Therefore, the time complexity of this function is O(n * (3^n)).

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