Define computational complexity and describe its importance in evaluating/comparing algorithms
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Computers and Technology, 21.02.2020 01:33 zoseta
Define computational complexity and describe its importance in evaluating/comparing algorithms
Explain the difference between empirical runtime analysis and computational complexity
How to determine the Big-O notation from the from T(n), the number of operations which is a function of n(the data size)?
Derive T(n) for the following iterative functions and determine Big-O
a.
def check(n):
if n%2==0:
return False
i = 3
ul = math. sqrt(n)
while i <= ul:
if n % i == 0:
return False
i += 2
return True
b.
def f1(array):
for i in range(len(array)):
item = array[i]
destination = i
while destination > 0 and array[destination - 1] >
item: array[destination] = array[destination - 1] destination -= 1
array[destination] = item
Derive T(n) for the following recursive functions and determine Big-O
a.
def check4(n):
if n % 4 > 1:
return n
return check4(n/4)
b.
def quickSort(arr, start, end):
if start < end:
pivot_index = partition(arr, start, end)
quickSort(arr, start, pivot_index - 1)
quickSort(arr, pivot_index + 1, end)
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