There are n unsorted arrays: A₁, A₂, ..., A_n. Assume that n is odd. Each of A₁, A₂, ..., A_n contains n distinct elements. There are no common elements between any two arrays. The worst-case time complexity of computing the median of the medians of A₁, A₂, ..., A_n is

The given diagram shows the flowchart for a recursive function $$A(n).$$ Assume that all statements, except for the recursive calls, have $$O(1)$$ time complexity. If the worst case time complexity of this function is $$O\left( {{n^\alpha }} \right),$$ then the least possible value (accurate up to two decimal positions) of $$\alpha $$ is ____________ .

An algorithm performs $${\left( {\log N} \right)^{1/2}}$$ find operations, N insert operations, $${\left( {\log N} \right)^{1/2}}$$ delete operations, and $${\left( {\log N} \right)^{1/2}}$$decrease-key operations on a set of data items with keys drawn from a linearly ordered set. For a delete operation, a pointer is provided to the record that must be deleted. For the decrease-key operation, a pointer is provided to the record that has its key decreased. Which one of the following data structures is the most suited for the algorithm to use, if the goal is to achieve the best total asymptotic complexity considering all the operations?

Consider the following C function.

int fun1 (int n) { 
     int i, j, k, p, q = 0; 
     for (i = 1; i < n; ++i) 
     {
        p = 0; 
       for (j = n; j > 1; j = j/2) 
           ++p;  
       for (k = 1; k < p; k = k * 2) 
           ++q;
     } 
     return q;
}

Which one of the following most closely approximates the return value of the function fun1?