The problem is equivalent to set cover, with univerise size log(max), and number of subsets simply N. So unless P = NP, your solution will be either exponential in N (just no...), or exponential in log(max), which could be more promising but seems difficult.

It's nothing new that GFG spreads around wrong solutions.

is this approach is correct?

1.First get total sum from the array using bit wise operator
2.After that sort the array
3.initialise a count = 0 variable and temp = arr[0]
4.loop through the sorted array(1..n):
       1.temp = temp|array[i]
       2.if(temp==sum):
           1.print(count)
           2.break
       3.else operate the next element to temp
5.end

A similar problem. XORSUB. just consider K = 0. and one possible solution for this is using Gaussian Elimination for XOR Maximization this will also satisfy the above constraints

Can we do this greedily by first storing the logical or of all numbers and then sorting the elements in decreasing order according to their popcount (in order decreasing number of set bits). and then if a[i]>maxOr -> i++ else we take or with it and push it into a set, after our number has become equal to the maxOR, we stop and return the size of set. Is this fine?