Navigating LeetCode’s Binary Tree Challenges: A Road Map to Mastery
Overview
Binary trees are fundamental data structures in computer science that play a pivotal role in various applications and algorithms. Their hierarchical and organized structure makes them versatile for efficient data storage, retrieval, and manipulation. In this blog post, we’ll explore the concept of binary trees, their characteristics, and delve into some essential algorithms associated with them.
Understanding Binary Trees:
A binary tree is a hierarchical data structure composed of nodes, where each node has at most two children, referred to as the left child and the right child. The topmost node in a binary tree is called the root, and nodes with no children are known as leaves. The connections between nodes are called edges.
The challenge covers critical topics such as path sum, binary tree properties, level order traversal, and binary tree manipulation. These are key areas that often appear in coding interviews, and mastering them contributes to a holistic understanding of binary trees. The final days of the challenge present participants with hard LeetCode problems, simulating the difficulty level often encountered in technical interviews. By completing the 10-day challenge, you’ll have honed your skills and be well-prepared to tackle even the toughest binary tree questions in interviews.
Solution To Below Challenges
Day 1/10 Leetcode Challenge
In-Order Traversal: Visit the left subtree, Process the root node,Visit the right subtree.
Pre-Order Traversal: Process the root node,Visit the left subtree,Visit the right subtree.
Post-Order Traversal: Visit the left subtree,Visit the rightsubtree,Process the root node.
94. Binary Tree Inorder Traversal
144. Binary Tree Pre Order Traversal
145. Binary Tree Post Order Traversal
589 N-ary Tree Pre Order Traversal
590. N-ary Tree Post Order Traversal
Day 2/10 Leetcode Challenge
The height of a tree is defined as the length of the longest path from the root to a leaf node. It is essentially the number of edges on the longest downward path from the root to a leaf.
The depth of a node in a tree is the length of the path from the root to that particular node. It is the number of edges on the path from the root to the node.
The diameter of a binary tree is the length of the longest path between any two nodes in a tree.
104. Maximum Depth of Binary Tree
111. Minimum Depth of Binary Tree
559. Maximum Depth of N-ary Tree
The “Compare Trees” problem on Leetcode generally involves comparing two binary trees and determining whether they are structurally identical or if they have the same values at corresponding nodes.
Day 3/10 Leetcode Challenge
Now, some easy Binary Tree problems that will help your thinking process.
1469.Find all lonely Nodes in Binary Tree
Day 4/10 Leetcode Challenge
Binary Search Tree The key property that distinguishes a BST is that for each node, all elements in its left subtree are less than or equal to the node, and all elements in its right subtree are greater than the node. This ordering property facilitates efficient search, insertion, and deletion operations.
653 Two Sum IV — Input is a BST
530. Minimum Absolute Difference in BST
783. Minimum Distance Between BST Nodes.
700. Search in a Binary Search Tree
230. Kth Smallest Element in BST
Day 5/10 Leetcode Challenge
Path Problem You are given root, you must perform operations on a path, (path is root to leaf).
Explore problems involving path sum in binary trees. Understand how properties like being a binary search tree or having unique paths impact problem-solving approaches.
1022 Sum of Root to Leaf Binary Numbers.
Day 6/10 Leetcode Challenge
Level Order Traversal: Visit all current level element before going to the next depth.
102 Binary Tree Level Order Traversal
103 Binary Tree Zigzag Level Order Traversal
116 Populating Next Right Pointer to Each Other
1161. Maximum Level Sum of a Binary Tree
314. Binary Tree Vertical Order Traversal
637. Average of Levels in Binary Tree.
199 Binary Tree Right Side View
Try Thinking for Left Side View , Top View and Botton View of Binary Tree
Day 7/10 Leetcode Challenge
Validate Tree The problem typically involves checking whether a binary tree satisfies the conditions of being a valid BST.
98. Validate Binary Search Tree
Ancestor Problems
The Lowest Common Ancestor (LCA) in a binary tree is the lowest (deepest) node that has both the given nodes as descendants. In other words, it’s the shared ancestor that is located farthest from the root.
A node is considered a common ancestor if both nodes p and q are descendants of that node.Lowest (Deepest) Common Ancestor: Among the common ancestors, the LCA is the one located farthest from the root, making it the lowest in terms of depth.
235. Lowest Common Ancestor of a Binary Search Tree
236. Lowest Common Ancestor of a Binary Tree
236. Lowest Common Ancestor of a Binary Tree II
1650. Lowest Common Ancestor of a Binary Tree — III
1123. Lowest Common Ancestor of Deepest Leaves
Day 8/10 Leetcode Challenge
Next is, given a combination of preorder, postorder and inorder traversals, you need to construct a binary tree/BST.
108. Convert Sorted array to Binary Search Tree.
105. Construct Binary Tree from Pre Order and in order Traversal
106. Construct Binary Tree from In Order and Post Traversal
Think of Construct Binary Tree from Pre Order and Post Traversal
Day 9/10 Leetcode Challenge
Some miscellaneous problems that you should look through:
114. Flatter Binary Tree to LinkedList
662. Maximum Width of Binary Tree
Day 10/10 Leetcode Challenge
Now, you almost Done try to solve some hard problems now.
124. Binary Tree Maximum Path Sum
Attached herewith is the solution for your reference.
Congratulations! By completing this 10-day Binary Tree Challenge, you’ve strengthened your grasp on binary tree concepts and polished your problem-solving skills. Remember, consistent practice is key to mastering any skill, and this challenge is a solid step towards acing your next binary tree-related coding interview. Good luck!
