(2) Algorithm f(n) if n==1 return 1; return 2*f(n-1)+ n*n*n;

Find the space complexity of the following code fib(int n) {   if (n <= 1) return n; return fib(n-1) + fib(n-2); }

II. Determine the big-O measure for each of the functions in the lower table. Choose from the various big-O measures in the upper table. A. O(1) G. O(Y) M. O(Y¹6) S. O(N log N) Y. O(W!) EE. O(X³Y) B. O(X) H. O(log Y) N. O(Z) T. O(N²) Z. O(67W) C. O(log X) I. O(Y log Y) O. 0(Z²) U. O(N²log N) AA. O(V) D. O(X log X) J. O(Y²) P. O(Z³) V. O(W³) BB. O(VV) E. O(X²) K. O(Y³) Q. O(log N) W. O(W⁹) CC. O(25¹) F. O(X³) L. O(Y¹5) R. O(N) X. O(9W) DD. O(XY)

Bottom: Given b, set the low-order b bits of x to 1; the others to 0. For example, if b is 3, x should be 7. Pay special attention to the edge cases: if b is 32 x should be −1; if b is 0 x should be 0. Do not use - in your solution. Write code in Java. Provided input(s): b Permitted: 40 operations (may use !, ~, +, <<, >>, &, ^, |) Hint: The obvious solution ~(0xFFFFFFFF << b) won’t work. Bit shifts always do a modulo on their right-hand operand, so a << b does the same thing as a << (b % (8*sizeof(a)). Thus, << 32 and << 0 do the same thing.

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10*/n + 5n*log(n) belongs to O e(n) O 0(n) O e(n²). O e(nxlog(n))