Sum of ranks in a binary tree - is there a better way - math

Question

Maybe this question does not belong as this is not a programming question per se, and i do apologize if this is the case.
I just had an exam in abstract data structures, and there was this question:
the rank of a tree node is defined like this: if you are the root of the tree, your rank is 0. Otherwise, your rank is the rank of your parents + 1.
Design an algorithm that calculates the sum of the ranks of all nodes in a binary tree. What is the runtime of your algorithm?
My answer I believe solves this question, my psuedo-code is as such:
int sum_of_tree_ranks(tree node x)
{
if x is a leaf return rank(x)
else, return sum_of_tree_ranks(x->left_child)+sum_of_tree_ranks(x->right_child)+rank(x)
}
where the function rank is
int rank(tree node x)
{
if x->parent=null return 0
else return 1+rank(x->parent)
}
it's very simple, the sum of ranks of a tree is the sum of the left subtree+sum of the right subtree + rank of the root.
The runtime of this algorithm I believe is n^2. i believe this is the case because we were not given the binary tree is balanced. it could be that there are n numbers in the tree but also n different "levels", as in, the tree looks like a linked list rather than a tree. so to calculate the rank of a leaf, potentially we go n steps up. the father of the leaf will be n-1 steps up etc...so thats n+(n-1)+(n-2)+...+1+0=O(n^2)
My question is, is this correct? does my algorithm solve the problem? is my analysis of the runtime correct? and most importantly, is there a better solution to solve this, that does not run in n^2?

Answer 1

Your algorithm works. your analysis is correct. The problem can be solved in O(n) time: (take care of leaves by yourself)
int rank(tree node x, int r)
{
if x is a leaf return r
else
return rank(x->left_child, r + 1)+ ranks(x->right_child, r + 1) + r
}
rank(tree->root, 0)

Answer 2

You're right but there is an O(n) solution providing you can use a more "complex" data structure.
Let each node hold its rank and update the ranks whenever you add/remove, that way you can use the O(1) statement:
return 1 + node->left.rank + node->right.rank;
and do this for each node on the tree to achieve O(n).
A thumb rule for reducing Complexity time is: if you can complex the data structure and add features to adapt it to your problem, you can reduce Complexity time to O(n) most of the times.

Answer 3

It can be solved in O(n) time where n is number of Nodes in Binary tree .
It's nothing but sum of height of all nodes where height of root node is zero .
As
Algorithm:
Input binary tree with left and right child
sum=0;
output sum
PrintSumOfrank(root,sum):
if(root==NULL) return 0;
return PrintSumOfrank(root->lchild,sum+1)+PrintSumOfRank(root->Rchild,sum+1)+sum;
Edit:
This can be also solved using queue or level order of traversal tree.
Algorithm using Queue:
int sum=0;
int currentHeight=0;
Node *T;
Node *t1;
if(T!=NULL)
enque(T);
while(Q is not empty) begin
currentHeight:currentHeight+1 ;
for each nodes in Q do
t1 = deque();
if(t1->lchild!=NULL)begin
enque(t1->lchild);sum = sum+currentHeight;
end if
if(t1->rchild!=NULL)begin
enque(t1->rchild);sum = sum+currentHeight;
end if
end for
end while
print sum ;