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Update index.md (#24020)

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Akshay Avinash
2019-02-27 20:59:08 +05:30
committed by Christopher McCormack
parent a3773d7c3a
commit 108884cbba
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guide/english/algorithms/binary-search-trees/index.md
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@ -47,9 +47,9 @@ It is very similar to the search function. You again start at the root of the tr
There are 3 cases that can happen when you are trying to delete a node. If it has, There are 3 cases that can happen when you are trying to delete a node. If it has,
1. No subtree (no children): This one is the easiest one. You can simply just delete the node, without any additional actions required. 1. No subtree (no children): This one is the easiest one. You can simply just delete the node, without any additional actions required.
2. One subtree (one child): You have to make sure that after the node is deleted, its child is then connected to the deleted node's parent. 2. One subtree (one child): You have to make sure that after the node is deleted, its child is then connected to the deleted node's parent.
3. Two subtrees (two children): You have to find and replace the node you want to delete with its successor (the leftfmost node in the right subtree). 3. Two subtrees (two children): You have to find and replace the node you want to delete with its inorder successor (the leftmost node in the right subtree).
The time complexity for creating a tree is `O(1)`. The time complexity for searching, inserting or deleting a node depends on the height of the tree `h`, so the worst case is `O(h)`. The time complexity for creating a tree is `O(1)`. The time complexity for searching, inserting or deleting a node depends on the height of the tree `h`, so the worst case is `O(h)` in case of skewed trees.
#### Predecessor of a node #### Predecessor of a node
Predecessors can be described as the node that would come right before the node you are currently at. To find the predecessor of the current node, look at the right-most/largest leaf node in the left subtree. Predecessors can be described as the node that would come right before the node you are currently at. To find the predecessor of the current node, look at the right-most/largest leaf node in the left subtree.