Find the Maximum Sum of Node Values

class Solution {
public:
    long long maxValSum(vector<int>& vals, int xor_key, vector<vector<int>>& connections) {
        long long totalSum = 0;
        int evenPosChanges = 0, smallestPosDiff = INT_MAX, largestNegDiff = INT_MIN;
            
        for (int val : vals) {
            int newVal = val ^ xor_key;
            totalSum += val;
            int delta = newVal - val;
                
            if (delta > 0) {
                smallestPosDiff = min(smallestPosDiff, delta);
                totalSum += delta;
                evenPosChanges++;
            } else {
                largestNegDiff = max(largestNegDiff, delta);
            }
        }
            
        if (evenPosChanges % 2 == 0)
            return totalSum;
            
        return max(totalSum - smallestPosDiff, totalSum + largestNegDiff);
    }
};

This solution in C++ provides a method to find the maximum sum of node values in a graph where nodes are represented by their values in a vector, and the edges are represented by another vector (of vectors) indicating connections, which is not used in the solving process. Here's a breakdown of the solution's main steps and logic:

1. Initialize totalSum to accumulate the sum of original node values.
2. Use evenPosChanges to track how many times the modified node value increased in comparison with the original node value.
3. Initialize smallestPosDiff and largestNegDiff to track the smallest positive difference and the largest negative difference, respectively.

Each node value is modified with an XOR operation against a given xor_key, and these steps are followed:

1. Iterate over each node value:
   • Compute the new value newVal by applying XOR with xor_key.
   • Compute the difference delta between the new value and the original value.
   • Update totalSum directly if this difference is positive and track it by updating smallestPosDiff.
   • If delta is negative, just update largestNegDiff.
2. After iterating over all nodes, check the number of positive modifications:
   • If evenPosChanges is even, return the totalSum as the answer because no further modifications need balance.
   • If it's odd, adjust totalSum using either smallestPosDiff or largestNegDiff based on which one maximizes the sum.

The answer is derived either directly from the sum of the modified values or adjusted to ensure the sum is maximized when considering necessary corrections for balance. This approach efficiently combines the properties of XOR manipulation with simple conditional checks and arithmetic operations to resolve the problem.

class Solution {
    public long calculateMaxSum(int[] values, int modifier, int[][] connections) {
        long accumulatedSum = 0;
        int numPositiveChanges = 0, minPositiveDiff = Integer.MAX_VALUE, maxNegativeDiff = Integer.MIN_VALUE;
    
        for (int value : values) {
            int adjustedValue = value ^ modifier;
            accumulatedSum += value;
            int changeDifference = adjustedValue - value;
            if (changeDifference > 0) {
                minPositiveDiff = Math.min(minPositiveDiff, changeDifference);
                accumulatedSum += changeDifference;
                numPositiveChanges++;
            } else {
                maxNegativeDiff = Math.max(maxNegativeDiff, changeDifference);
            }
        }
    
        if (numPositiveChanges % 2 == 0) {
            return accumulatedSum;
        }
    
        return Math.max(accumulatedSum - minPositiveDiff, accumulatedSum + maxNegativeDiff);
    }
}

You will calculate the maximum sum of node values from an array, considering a specific modifier and connections.

Start by defining a calculateMaxSum method in your Java program that takes an array of integers (values), a modifier integer, and a matrix of integer arrays (connections). This method will return the maximum possible accumulated sum of node values after adjustments with bitwise operations and mathematical calculations.

• Follow these principles in your code to achieve the required result:

  • Initialize accumulatedSum to keep track of the total value before and after adjustments.
  • Use numPositiveChanges to count how many times a node value increases after adjustment.
  • minPositiveDiff stores the smallest positive change, and maxNegativeDiff stores the largest negative change between the original and adjusted values.

• For each value in the values array:

  1. Apply a bitwise XOR operation between the value and the modifier to get adjustedValue.
  2. Add the original value to accumulatedSum.
  3. Calculate the difference (changeDifference) between adjustedValue and the original value.
  4. If changeDifference is positive, update minPositiveDiff and additional adjustments to accumulatedSum. Increase the numPositiveChanges counter.
  5. If changeDifference is negative, update maxNegativeDiff with the maximum decrease.

• Post-process the results:

  • If the count of positive changes is even, the accumulated sum is maximized as it is.
  • If the count is odd, compare and return the greater value between reducing the minimum positive difference from the accumulatedSum or adding the maximum negative difference to it.

This method efficiently consolidates the node values factoring in potential adjustments dictated by the modifier and provides the maximum possible sum under given conditions.

class Solution:
    def findMaxValue(self, elements: List[int], offset: int, connections: List[List[int]]) -> int:
        totalSum = 0
        positiveCount = 0
        smallestPositive = 1 << 30
        largestNegative = -1 * (1 << 30)
    
        for value in elements:
            transformedValue = value ^ offset
            totalSum += value
            delta = transformedValue - value
            if delta > 0:
                smallestPositive = min(smallestPositive, delta)
                totalSum += delta
                positiveCount += 1
            else:
                largestNegative = max(largestNegative, delta)
    
        # Return even positive deltas' total sum.
        if positiveCount % 2 == 0:
            return totalSum
    
        # Return max total considering adjustments.
        return max(totalSum - smallestPositive, totalSum + largestNegative)

The provided Python code defines a method findMaxValue to find the maximum sum of node values based on input elements, an offset, and connections.

Exploring Logic:

• The method initializes the totalSum of all node values, and variables to track the smallest positive delta (smallestPositive) and the largest negative delta (largestNegative).
• Iterates through each element in the elements list, computes transformedValue as the XOR of the element with the offset, and includes the original value in totalSum.
• Computes the delta as the difference between transformedValue and the original value.
  • If the delta is positive, it updates the smallestPositive and the positive count while adding the delta to totalSum.
  • If the delta is negative, updates the largestNegative.
• After processing all elements:
  • If the count of positive deltas is even, it simply returns totalSum.
  • If odd, it determines the maximum sum either by subtracting the smallest positive or adding the largest negative to the totalSum.

Application Insights:

• The code handles adjustments based on whether the transformation increases or decreases the node value and carefully ensures the maximum sum is achieved under defined constraints.
• This method's versatility in adapting to differences generated by XOR operations and its cautious approach to edge cases can be robust for scenarios involving data transformation and optimization.

This outline helps understand the core functionality of calculating a potentially maximized sum by considering altered values in terms of bitwise operations and balancing those modifications against an overall measurement of change (either positive or negative).