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Parity Flag Map

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Your task in Parity Flag Map is to help operations spot stable sensor points. You're given an array of integers representing sensor readings, and you need to create a parallel boolean map. For each reading, you'll mark true if it's even ("calm") and false if it's odd ("fluctuation").

The "secret sauce" here is Boolean Mapping. You scan the input and build a fresh boolean result without altering the original data. Negative numbers follow standard parity rules, and an empty input results in an empty map. This transformation provides a quick reference for analysts to scan, making it easy to spot alternating spikes or long periods of calm at a glance. It's a fundamental data processing skill that turns complex numbers into simplified, high-level signals for rapid team analysis!

Keep the algorithm focused on one clear invariant and update path so correctness is easy to verify from left to right. This reduces accidental branching errors and helps ensure the final output stays consistent with the problem contract across random and adversarial test shapes.

Examples

Example 1
Input
nums = [1,3,5]
Output
[false,false,false]
Explanation

All numbers are odd.

Example 2
Input
nums = []
Output
[]
Explanation

No readings mean no flags.

Example 3
Input
nums = [2,5,6,3]
Output
[true,false,true,false]
Explanation

Even numbers (2,6) produce true entries.

Algorithm Flow

Recommendation Algorithm Flow for Parity Flag Map - Budibadu
Recommendation Algorithm Flow for Parity Flag Map - Budibadu

Best Answers

java
import java.util.stream.IntStream;
class Solution {
    public Object parity_flags(Object nums) {
        int[] arr = (int[]) nums;
        return IntStream.of(arr).map(n -> n % 2).toArray();
    }
}