#codingexercise
Write an efficient program to reverse the bits of a number.
We do this by looping through the number and testing each bit. If the bit is set at position i then we set the bit at total_number_of_possible_bits -1 - i in the reverse number.
unsigned int reverseBits(unsigned int num)
{
unsigned int number_of_possible_bits = sizeof(num) * 8;
unsigned int reverse_num = 0;
for (int i = 0; i < number_of_possible_bits; i++)
{
int temp = (num & (1 << i );
if (temp)
    reverse_num |= (1 << ((number_of_possible_bits - 1) - i));
}
return reverse_num;
}

Another coding interview question is how to count the number of binary search trees that are within a numerical range?.
This can be found by performing  a  traversal
If the subtrees are in range the root is also in range.

bool getCount(Node root, ref count)
{
if (root == NULL) return true;
Bool l = false;
Bool r = false;
if (root.left) l = getCount(root.left, count);
if (root.right) r = getCount(root.right, count);
if ( l && r && inRange(root.left, root.right))
  count++
return false;
}

Another interview problem is schedule a meeting
Given an employee array of a large number of employees, find a window of time with maximum duration for a meeting that suits all the employees in the input.
Since each employee has different availabilities we can first find the availability ranges for each employee. This may result in a number of time Slots greater than the number of employees. Then taking time as increments of  time slices such as a minute, we can write them down as sequences. After that we can find the longest common subsequence. This approach can scale to any length and number of time range of employees when the time slice increments are more granular. It also finds a maximum number of employees who can make it to a meeting when all cannot.

This problem can be attempted in many ways but we focus on one based on max flow algorithm. The reason we choose maximum flow is because we want to find the window that is maximum.  We consider Ford Fulkerson algorithm.
Before using Ford Fulkerson, we have to transform the problem from multisource multisink to single source single sink by adding a consolidated source and a consolidated sink.  Each flow is considered as a viability for an employee and the max flow is when we can augment this flow for all the employees. We consider granular time slots for augmenting this maximum flow. Then we add increment timeslots for maximum duration of the meeting.