Learn and practice the Tree Depth-First Search and Tree Breadth-First Search patterns to solve coding interview problems.

Grokking Grind 75 in Python: Mastery through Coding Patterns

Trees play a pivotal role in organizing hierarchical data, optimizing searches, and solving complex problems. In this module, we’ll learn to choose the appropriate tree for a given problem and apply the more appropriate of the two major traversal techniques, breadth-first or depth-first, to solve it.

Trees

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## Statement

Given a binary search tree with $n$ nodes, your task is to find the lowest common ancestor of two of its nodes, `node1` and `node2`.

The lowest common ancestor of two nodes, `node1` and `node2`, is defined as the lowest node in the binary search tree that has both `node1` and `node2` as descendants.

By definition, a node is a descendant of itself. For example, if `node2` is a descendant of `node1`, and we know that `node1` is a descendant of itself, then `node1` will be the lowest common ancestor of `node1` and `node2`.

**Constraints:**

* $2 \leq n \leq 500$
* $-10^3 \leq$ `Node.data` $\leq 10^3$
* All `Node.data` are unique.
* `node1` $\neq$ `node2`
* `node1` and `node2` exist in the tree.

## Examples

Try to solve the Lowest Common Ancestor of a Binary Search Tree problem.

Tree Depth-first Search

Tree Breadth-first Search

Conclusion

Lowest Common Ancestor of a Binary Search Tree

Statement