Maximum Level Sum of a Binary Tree - Solution & Explanation

The BFS approach is well-suited for problems involving levels of a binary tree. We will use a queue to process the tree level by level, keeping track of the sum of node values at each level. We will maintain a variable to store the maximum sum encountered and the level corresponding to this maximum sum. By processing level by level, we ensure that when we find a new maximum, it is the smallest level with that sum.

This implementation uses a queue to traverse the binary tree level by level. For each level, we calculate the sum of its node values. If this sum is greater than the previously recorded maximum sum, we update the maximum sum and note the level number. The queue helps ensure that each node of a given level is processed before nodes of the next level, which is key to implementing BFS.

This approach involves using a DFS traversal to explore the tree. We pass the current depth as a parameter to each recursive call and maintain an array or dictionary to track the sum of values at each level. After the traversal, we determine which level has the highest sum. DFS allows us to explore the tree deeply, and since each call carries a depth count, we can easily track levels.

The Python solution uses DFS by recursively traversing the tree and tracking the sum of node values at each level using a dictionary. After completing the traversal, it identifies the level with the maximum sum.