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Best Case: If the list is sorted already then A[i] <= key at line 4. Thus, rest of the lines in the inner loop will not execute. Then,
T (n) = c1n + c2 (n -1) + c3(n -1) + c4 (n -1) = O (n), which indicates that the time complexity is linear.
Worst Case: This case arises while the list is sorted in reverse order. Thus, for execution of line 1, the Boolean condition at line 4 will be true.
So, step line 4 is executed
T (n) = c1n + c2(n -1) + c3(n -1) + c4 (n(n+1)/2 - 1) + c5(n(n -1)/2) + c6(n(n-1)/2) + c7 (n -1)
= O (n2).
Average case: In mostly cases, the list will be into some random order. That is, it neither sorted in descending or ascending order and the time complexity will lie somewhere among the best & the worst case.
T (n) best < T(n) Avg. < T(n) worst
Q. What do you mean by the best case complexity of quick sort and outline why it is so. How would its worst case behaviour arise?
You are given two jugs, a 4-gallon one and a 3-gallon one. Neither has any measuring marker on it. There is a tap that can be used to fill the jugs with water. How can you get exac
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