PART 1 : Analyze the following algorithms. Write worst-case, average-case, base-case analysis if significant. Express your results using most proper asymptotic notation. Explain your solutions. For the 1st to the 4th algorithms use table method and show table.
1.
somefunction(rows, cols)
{
for(i = 1; i <= rows; i++)
{
for( j = 1; j <= cols; j++)
print(*)
print(newline)
}
}
2.
somefunction(a, b)
{
if (b == 0)
return 1
answer = a
increment = a
for(i = 1; i < b; i++)
{
for(j = 1; j < a; j++)
{
answer += increment
}
increment = answer
}
return answer
}
3.
somefunction(arr[], arr_len)
{
val = 0
for (i = 0; i < arr_len / 2; i++)
val = val + arr[i]
for (i = n / 2; i < arr_len; i++)
val = val – arr[i]
if (val >= 0)
return 1
else
return –1
}
4.
somefunction(n)
{
c = 0
for (i = 1 to n*n)
for (j = 1 to n)
for (k = 1 to 2*j)
c = c+1
return c
}
5.
otherfunction(xp, yp)
{
temp = xp
xp = yp
yp = temp
}
somefunction(arr[], arr_len)
{
for (i = 0; i < arr_len - 1; i++)
{
min_idx = i
for (j = i+1; j < arr_len; j++)
if (arr[j] < arr[min_idx])
min_idx = j
otherfunction(arr[min_idx], arr[i])
}
}
6.
otherfunction(a, b)
{
if b == 0:
return 1
answer = a
increment = a
for i = 1 to b:
{
for j = 1 to a:
answer += increment
increment = answer
}
return answer
}
somefunction(arr, arr_len)
{
for i = 0 to arr_len):
for j = i to arr_len):
if otherfunction(arr[i], 2) == arr[j]:
print(arr[i], arr[j])
elif otherfunction(arr[j], 2) == arr[i]:
print(arr[j], arr[i])
}
7.
otherfunction(X, i)
{
s = 0
for(j = 0; j <= i; j=j*2)
s = s + X[j]
return s
}
somefunction(arr[], arr_len)
{
for(i = 0; i <= arr_len-1; i++)
A[i] = otherfunction(arr, i) / (i + 1)
return A
}
8.
somefunction(n)
{
res = 0
j = 1
if(n < 10)
return n + 10
for(i = 9; i >= 1; i--)
while (n % i == 0)
n = n / i
res = res + j * i
j *= 10
if(n > 10)
return -1
return res
}
PART 2 : Design an algorithm for each of the problems. Write your algorithms in pseudo code. Obtain the complexities of the algorithms. Write worst-case, average-case, base-case analysis if significant. Express your results using most proper asymptotic notation. Explain your solutions.
1. Assume you have an array of points in 2d space. Find the closest point in the array to a given point.
2. The ith element of an array A is a local minimum if, A[i] <= A[i+1] and A[i] <= A[I-1].
a. Find a local minimum in a given array A.
b. Find all local minimums in a given array A.
3. Find if a given array of integers contains two numbers whose sum is a given number b.
4. A sequence of positive integers in increasing order, a1, a2,…,an is called a “Sum Chain of Length n” if for all k (1 < k ≤ n), there exist i, j (1 ≤ i ≤ j ≤ k) such that ak=ai+aj
Example: {1, 2, 3, 5, 10, 13, 15} : (2=1+1, 3=2+1, 5=3+2, 10=5+5, 13=10+3, 15=10+5)
Find if a given sequence of n numbers is a “Sum Chain of Length n”. Use the algorithm you design for the third question in this part.
