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Trees Problems

Tree problems — DFS and BFS traversal, BST validation, path sums, and tree construction from traversals.

Easy · 4

Maximum Depth of Binary Treeeasy Same Treeeasy Invert Binary Treeeasy Subtree of Another Treeeasy

Medium · 5

Binary Tree Level Order Traversalmedium Construct Binary Tree from Preorder and Inorder Traversalmedium Validate Binary Search Treemedium Kth Smallest Element in a BSTmedium Lowest Common Ancestor of a Binary Search Treemedium

Hard · 2

Binary Tree Maximum Path Sumhard Serialize and Deserialize Binary Treehard

Tree problems split cleanly into traversal (visit every node in a useful order) and structural (verify or modify the tree's shape). Mastering both is essential because trees come up in nearly every interview round — and the recursion patterns transfer directly to graph and dynamic-programming problems.

The four traversal orders — inorder, preorder, postorder, and level-order — each unlock a different class of problems. Inorder gives sorted output on a BST, postorder is the basis for tree DP and "compute child results before parent" patterns, level-order (BFS with a queue) is the basis for shortest-path and width problems. Knowing which traversal applies is half the work; the other half is implementing it cleanly with recursion.

The Ratta tree track covers Invert Binary Tree, Maximum Depth, Same Tree, Subtree of Another Tree, Lowest Common Ancestor, Level Order Traversal, Validate BST, Kth Smallest in BST, and Construct Tree from Preorder and Inorder. Every problem ships with the recursive solution, the iterative variant where useful, and full implementations in C++, Java, Python, and Go.

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