Lowest Common Ancestor of BST
Detailed guide and Python implementation for the 'Lowest Common Ancestor of BST' problem.
1. Concept Overview
The 'Lowest Common Ancestor of BST' problem is a key challenge in the Trees section.
This implementation focuses on easy-level logic in Python.
We prioritize technical accuracy and code readability in our provided solutions.
2. Real-World Applications
3. Visual Intuition
Visualizing the logic flow for Lowest Common Ancestor of BST.
4. Prerequisites
5. Step-by-Step Thinking
1. Understand the problem
Read the problem statement for Lowest Common Ancestor of BST carefully.
2. Formulate brute force
Draft a simple iterative solution.
3. Identify inefficiency
Look for redundant calculations.
4. Optimize search path
Use hashing or sorting to speed up the process.
5. Final Implementation
Clean up the code for production standards.
Problem Statement
Given a binary search tree (BST), find the lowest common ancestor (LCA) node of two given nodes in the BST.
According to the definition of LCA: "The lowest common ancestor is defined between two nodes p and q as the lowest node in T that has both p and q as descendants (where we allow a node to be a descendant of itself)."
The BST is represented as a level-order list. Implement a function lowestCommonAncestor(root: list, p: int, q: int) -> int that returns the value of the LCA node.
- •The number of nodes in the tree is in the range [2, 100000]
- •-1000000000 <= Node.val <= 1000000000
- •All Node.val are unique
- •p != q
- •p and q will exist in the BST
Examples
[6,2,8,0,4,7,9,None,None,3,5], 2, 8
6
The LCA of nodes 2 and 8 is 6, which is the root.
[6,2,8,0,4,7,9,None,None,3,5], 2, 4
2
The LCA of nodes 2 and 4 is 2, since a node can be a descendant of itself.
[2,1], 2, 1
2
The LCA of nodes 2 and 1 is 2.
Need a Hint?
Edge Cases to Watch
- Empty input structures
- Single element inputs
- Large numerical bounds
Ready to Solve?
Open the problem in PyRun's browser-based Python editor. Your code runs fully offline — no server required.
Interview Insights & Variations
Complexity Analysis Breakdown
Why Time: Directly evaluates all possibilities.
Why Space: Uses standard local memory.
Why Time: Optimized paths reduce total operations.
Why Space: May trade memory for speed.
Optimized Solution Python Code
Optimized Solution Python Code
def lowest_common_ancestor_opt(root, p, q):
if isinstance(root, list):
r = build_tree(root)
val_p = p[0] if isinstance(p, list) else p
val_q = q[0] if isinstance(q, list) else q
def find_node(node, val):
if not node: return None
if node.val == val: return node
return find_node(node.left, val) or find_node(node.right, val)
node_p = find_node(r, val_p) or TreeNode(val_p)
node_q = find_node(r, val_q) or TreeNode(val_q)
res = lowest_common_ancestor_opt_helper(r, node_p, node_q)
return res.val if res else None
return lowest_common_ancestor_opt_helper(root, p, q)
def lowest_common_ancestor_opt_helper(root: TreeNode, p: TreeNode, q: TreeNode) -> TreeNode:
curr = root
while curr:
if p.val > curr.val and q.val > curr.val:
curr = curr.right
elif p.val < curr.val and q.val < curr.val:
curr = curr.left
else:
return currBrute Force Code (Spoiler Guarded)
Brute Force Code (Spoiler Guarded)
def lowest_common_ancestor_brute(root, p, q):
if isinstance(root, list):
r = build_tree(root)
val_p = p[0] if isinstance(p, list) else p
val_q = q[0] if isinstance(q, list) else q
def find_node(node, val):
if not node: return None
if node.val == val: return node
return find_node(node.left, val) or find_node(node.right, val)
node_p = find_node(r, val_p) or TreeNode(val_p)
node_q = find_node(r, val_q) or TreeNode(val_q)
res = lowest_common_ancestor_brute_helper(r, node_p, node_q)
return res.val if res else None
return lowest_common_ancestor_brute_helper(root, p, q)
def lowest_common_ancestor_brute_helper(root: TreeNode, p: TreeNode, q: TreeNode) -> TreeNode:
if not root or root == p or root == q:
return root
left = lowest_common_ancestor_brute_helper(root.left, p, q)
right = lowest_common_ancestor_brute_helper(root.right, p, q)
if left and right:
return root
return left or rightAlgorithm Pattern Checklist
When dealing with Trees data patterns.
Core Prerequisites
Revision Key Notes
Common Mistakes & Pitfalls
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