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Binary search tree in data structure
Hi, in this is part 3 of the tree data structure, we're going to discuss the Binary search tree, and in the next post, we will cover in detail its implementation (insertion, searching, and deletion).
- Binary search tree: or (sorted binary tree) is a binary tree invented in (1960) which all nodes that exist in the right sub-tree are greater than the nodes that exist in the left sub-tree and there parent node. and Both the left and right subtrees must be binary search trees as well.
- The space complexity of the binary search tree is O(n) where n is the number of elements.
insert | search | delete | |
---|---|---|---|
best case | O(log n) | O(log n) | O(log n) |
worst case | O(n) | O(n) | O(n) |
The time complexity of the Binary search tree becomes O(n) if the binary tree is a skewed binary tree.
- Faster than array and Linked list in insertion and deletion.
- It is so Efficient in searching
- getting The minimum and the Maximum easily
- More stack space due to the recursion
- The run time mat increases because of the comparisons.
- https://www.geeksforgeeks.org/binary-search-tree-set-1-search-and-insertion/
- https://afteracademy.com/blog/binary-search-tree-introduc tion-operations-and-applications
- https://www.quora.com/What-are-some-practical-applications-of-binary-search-trees
- https://www.upgrad.com/blog/binary-tree-in-data-structure/
- https://www.coursehero.com/file/p1fldsp9/Disadvantages-of-Binary-Search-Trees-The-shape-of-the-tree-depends-on-the-order/
- https://www.javatpoint.com/binary-search-tree
See you in the next post, on which we will cover the binary search tree implementation in detail, Happy Coding:)
#day_15
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