DAY 61 Binary Tree DFS: Depth and Similarity

Hello Everyone!

Week 13 started with a focus on Binary Tree Problems Using Depth-First Search (DFS). Today’s tasks required exploring binary tree structures to calculate depths and compare nodes, showcasing the elegance of recursive and iterative tree traversal. It felt like diving into a hierarchical world, understanding its structure step by step.

How the Day Played Out

1. Maximum Depth of Binary Tree (Easy Difficulty)

   • Calculate the maximum depth of a binary tree.
   • The Strategy:
     • Used DFS recursively to traverse the tree.
     • At each node, calculated the depth by taking the maximum of the depths of the left and right subtrees, adding 1 for the current node.
   • The Fun Part:
     • Watching the recursion unfold and the depth stack build dynamically felt like exploring levels of a virtual tree.

2. Leaf-Similar Trees (Medium Difficulty)

   • Determine if two binary trees are leaf-similar, meaning they have the same leaf sequence.
   • The Strategy:
     • Used DFS to traverse both trees, collecting the leaf nodes in lists.
     • Compared the lists to check if the leaf sequences matched.
   • The Fun Part:
     • Extracting and comparing the leaf sequences was like finding and matching hidden treasures within the trees.

What Made Today Special

1. Recursive Elegance:

   • Both problems showcased the power of recursion in traversing hierarchical structures efficiently.

2. Comparative Analysis:

   • Leaf-Similar Trees emphasized the importance of comparing data extracted during traversal, adding depth to the problem-solving process.

3. Visualizing Trees:

   • Thinking of the binary tree as a hierarchical map made the traversal process intuitive and engaging.

Key Takeaways

• DFS Simplifies Tree Traversals:

  • Problems like Maximum Depth of Binary Tree highlight how DFS elegantly explores hierarchical structures to compute properties like depth.

• Data Collection Matters:

  • In Leaf-Similar Trees, collecting and comparing data from DFS traversals shows how extracted information can guide solutions.

• Recursive Thinking is Powerful:

  • Recursion allows for clear and concise traversal logic, reducing the complexity of tree-based problems.

Reflections

The Maximum Depth of Binary Tree problem was a satisfying warm-up that reinforced the basics of recursive traversal, while Leaf-Similar Trees added a layer of complexity with its comparative analysis. Together, these tasks showcased the versatility of DFS in solving binary tree problems efficiently.

What’s Next?

Tomorrow, I’ll continue with Binary Tree DFS Problems, tackling Count Good Nodes in Binary Tree and Path Sum III. These tasks will test my ability to track values dynamically and calculate paths with specific properties.

Thank you for following along! Let’s keep solving, learning, and growing together.