Find the complexity of the traditional algorithms as Big O notation: - Find the total of the array elements sum(a, n) { } { result= 0 } for i=1 to n if (result < a[i]) result = a[i] - Find the maximum element of the array max(a, n) return result total = 0 for i=1 to n total = total + a[i] return total Write the above algorithms as a function and test the functions by using randomly generated values. Type of array elements can be int. You can use any programming language you know

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Find the complexity of the traditional algorithms as Big O notation:
- Find the total of the array elements
sum(a, n)
{
}
{
result = 0
}
for i=1 to n
if (result < a[i])
result = a[i]
- Find the maximum element of the array
max(a, n)
return result
total = 0
for i = 1 to n
total = total + a[i]
return total
Write the above algorithms as a function and test the functions by using randomly generated values. Type of array
elements can be int. You can use any programming language you know
Transcribed Image Text:Find the complexity of the traditional algorithms as Big O notation: - Find the total of the array elements sum(a, n) { } { result = 0 } for i=1 to n if (result < a[i]) result = a[i] - Find the maximum element of the array max(a, n) return result total = 0 for i = 1 to n total = total + a[i] return total Write the above algorithms as a function and test the functions by using randomly generated values. Type of array elements can be int. You can use any programming language you know
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