Reference no: EM132354757

Question

For each function, a rough analysis of its running time in terms of n (where n is the length of the input list a, i.e. n=len(a)) and where n=10,000.

For example, if your function looks like this: def riddle(a): s=0 for x in a: for y in a: s = s+ x*y return s Then you would write: This function has two nested for loops. The inner loop executes 10,000 times for each step of the outer loop, which also executes 10,000 times.

Therefore, this function performs roughly 10,000*10,000=100,000,000 operations. If your function uses python's sort() method or python's sorted() function to sort the list a, just say that that function call does about 140,000 operations (since python's sort does roughly n log_2 n operations).

Alternatively, if you prefer, you can write your analysis in terms of general n. Thus for the above function riddle, one would say that its running time is O(n^2).

Write a function, largest_34(a), that returns the sum of the 3rd and 4th largest values in the list a. For simplicity, you may assume that the numbers in the list a are all distinct and that the list a has at least 4 elements. For example: >>> largest_34([1000, 1, 100, 2, 99, 200, -100]) 199.