There are n components, and the performance level of each component is represented by performance[0], performance[1], ..., performance[n-1].
Let's define a partition (l, r) as the group of components indexed from l to r. To identify and resolve potential bottlenecks in the system, the engineer needs to compute the bitwise AND operation for all components within a partition. The bottleneck level of a partition (l, r) is expressed as:
f(l,r) = performance[l] & performance[l+1] & ... & performance[r]
Here, the & operator represents the bitwise AND operation.
The goal of the engineers is to divide the components into contiguous partitions, ensuring each component belongs to exactly one partition. The objective is to minimize the total bottleneck level of the partitions while maximizing the number of partitions.
Given an integer array performance of size n, determine the maximum number of partitions that can be achieved while minimizing the total bottleneck levels of the partitions.
performance = [5, 2, 6, 1, 1, 4] return = 3
Example n=6
performance = [5, 2, 6, 1, 1, 4]
Index Range (l, r) for the partitions
Bottleneck Level
(0, 1) - (performance[0] & performance[1]) = (5 & 2) = 0
(2, 3) - (performance[2] & performance[3]) = (6 & 1) = 0
(4,5) - (performance[4] & performance[5]) = (1 & 4) = 0
Hence 3 partitions.
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public int maximizePartitions(int[] performance) {
// write your code here
}