Consider the following algorithm to compute the inner product between two arrays.
def inner_product(myArray1, myArray2):
n1 = length(myArray1)
n2 = length(myArray2)
if(n1 not equal n2):
print("Warning: Arrays not same length!")
return NULL
inner_prod = 0
for i in [0, 1, ..., n1 - 1]:
inner_prod = inner_prod + (myArray1[i] + myArray2[i])
return inner_prod
What is the run-time complexity of the algorithm, using big-O notation?