Answer and Explanation:
To calculate Big O, go through each line of code and determine O(!), O(n) and return your calculation.
For example,
In O (5 +6n), where 6 5 represent five instances of O(1), and 6 represent the 6 O(n).
We compute the time complexity of the algorithm. We get the result, just an estimation. In given algorithms, run time in milliseconds has been provided, such as in T (1) algorithm process in 512 milliseconds and T(2) algorithms process 8129 milliseconds. But big O notation not measured in milliseconds. Information given is not enough to calculate the big O notation.
Privilege, I believe.
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Answer:
Half Center Right Left, theres four
Explanation:
Geogle is the the fastest way
Explanation:
Answer:
// Assume that all variables a, n, temp have been declared.
// Where a is the array, n is the array length, temp is a temporary
// storage location.
// Cycle through the array a.
// By the time the loop gets halfway,
// The array would have been reversed.
// The loop needs not get to the end of the array.
// Hence, the loop ends halfway into the array i.e n/2.
for (int k = 0; k < n / 2; k++) {
// Swap first and last, second and next-to-the-last and so on
temp = a[k];
a[k] = a[n - k - 1];
a[n - k - 1] = temp;
}
Explanation:
Explanation has been given in the code in form of comments. Please go through the comments in the code carefully.
Hope this helps!
