Why Top View of Binary Tree in DSA Java?

The Big Idea

Discover how to see the hidden shape of a tree from above without confusion!

The Scenario

Imagine you have a tall tree in your backyard, and you want to see which branches are visible if you look at it from the top. If you try to list these branches by walking around the tree and guessing, it gets confusing quickly.

The Problem

Manually figuring out which parts of the tree are visible from above is slow and error-prone because branches can overlap when viewed from the top. Without a clear method, you might miss some branches or count some twice.

The Solution

The top view of a binary tree shows exactly which nodes are visible when looking from above. Using a simple algorithm, we can find these nodes by tracking horizontal positions and levels, making the problem easy and clear.

Before vs After

✗ Before

void printTopView(Node root) {
  // Manually guess visible nodes
  System.out.println(root.data);
  // No systematic way to check others
}

✓ After

void printTopView(Node root) {
  Map<Integer, Integer> topViewMap = new TreeMap<>();
  Queue<Pair<Node, Integer>> queue = new LinkedList<>();
  queue.add(new Pair<>(root, 0));
  while (!queue.isEmpty()) {
    Pair<Node, Integer> current = queue.poll();
    if (!topViewMap.containsKey(current.getValue())) {
      topViewMap.put(current.getValue(), current.getKey().data);
    }
    if (current.getKey().left != null) {
      queue.add(new Pair<>(current.getKey().left, current.getValue() - 1));
    }
    if (current.getKey().right != null) {
      queue.add(new Pair<>(current.getKey().right, current.getValue() + 1));
    }
  }
  topViewMap.values().forEach(System.out::println);
}

What It Enables

This concept lets you clearly see the unique nodes visible from the top, helping in visualization and solving complex tree problems easily.

Real Life Example

In city planning, when designing a skyline view, you want to know which buildings are visible from above. The top view concept helps model this by showing only the visible parts.

Key Takeaways

Manual guessing of top view is confusing and unreliable.

Top view uses horizontal distances to find visible nodes systematically.

This helps in clear visualization and solving tree-related problems.

Practice

1. What does the top view of a binary tree represent?

easy

A. Nodes visible when the tree is viewed from the right side

B. Nodes visible when the tree is viewed from the left side

C. Nodes visible when the tree is viewed from the top

D. All leaf nodes of the tree

Solution

1. Step 1: Understand the top view concept

   The top view of a binary tree includes all nodes visible when looking down vertically from above the tree.

2. Step 2: Compare with other views

   Left view shows nodes from the left side, right view from the right side, and leaf nodes are only the bottom nodes. So, only top view matches nodes visible from above.

3. Final Answer:

   Nodes visible when the tree is viewed from the top -> Option C

4. Quick Check:

   Top view = nodes seen from above [OK]

Hint: Top view shows nodes visible from above the tree [OK]

Common Mistakes:

• Confusing top view with left or right view
• Thinking top view includes all leaf nodes
• Assuming top view is the same as level order traversal

2. Which data structure is commonly used to store nodes while computing the top view of a binary tree in Java?

easy

A. Stack

B. ArrayList

C. HashMap

D. Queue

Solution

1. Step 1: Identify traversal method for top view

   Top view is usually found using level order traversal, which requires a queue to process nodes level by level.

2. Step 2: Understand role of other data structures

   HashMap is used to store horizontal distances but queue is essential to traverse nodes in order. Stack and ArrayList are not suitable for level order traversal.

3. Final Answer:

   Queue -> Option D

4. Quick Check:

   Level order traversal uses queue [OK]

Hint: Use queue for level order traversal in top view [OK]

Common Mistakes:

• Using stack instead of queue for traversal
• Confusing storage with traversal data structure
• Ignoring the need for horizontal distance mapping

3. What is the output of the top view traversal for the following binary tree?

        1
       / \
      2   3
       \   \
        4   5
         \   \
          6   7

medium

A. [2, 1, 3, 4, 7]

B. [2, 1, 3, 5, 7]

C. [2, 1, 4, 6, 7]

D. [1, 2, 3, 4, 5]

Solution

1. Step 1: Assign horizontal distances (HD) to nodes

   Root (1) has HD=0, left child (2) HD=-1, right child (3) HD=1. Node 4 is right child of 2, HD=0. Node 5 is right child of 3, HD=2. Node 6 is right child of 4, HD=1. Node 7 is right child of 5, HD=3.

2. Step 2: Select first node at each HD from top to bottom

   At HD=-1: 2, HD=0: 1, HD=1: 3, HD=2: 5, HD=3: 7. Nodes 4 and 6 are hidden behind 1 and 3 respectively.

3. Final Answer:

   [2, 1, 3, 5, 7] -> Option B

4. Quick Check:

   Top view nodes by HD = [2,1,3,5,7] [OK]

Hint: Pick first node at each horizontal distance [OK]

Common Mistakes:

• Including nodes hidden behind others at same horizontal distance
• Mixing order of nodes in output
• Ignoring horizontal distance calculation

4. Identify the error in this Java snippet for top view of a binary tree:

Map map = new HashMap<>();
Queue<Node> queue = new LinkedList<>();
queue.add(root);
while (!queue.isEmpty()) {
  Node temp = queue.poll();
  int hd = temp.hd;
  if (!map.containsKey(hd)) {
    map.put(hd, temp.data);
  }
  if (temp.left != null) {
    temp.left.hd = hd - 1;
    queue.add(temp.left);
  }
  if (temp.right != null) {
    temp.right.hd = hd + 1;
    queue.add(temp.right);
  }
}

medium

A. Horizontal distance (hd) is not initialized for root node

B. Using HashMap instead of TreeMap causes wrong order

C. Queue should be a Stack for correct traversal

D. map.put overwrites existing keys causing wrong output

Solution

1. Step 1: Check initialization of horizontal distance

   The root node's horizontal distance (hd) must be set before adding to queue. Here, root.hd is not initialized, so hd is zero by default or undefined.

2. Step 2: Understand impact of missing hd initialization

   Without root.hd set, all subsequent hd calculations are incorrect, leading to wrong top view nodes.

3. Final Answer:

   Horizontal distance (hd) is not initialized for root node -> Option A

4. Quick Check:

   Root hd must be set before traversal [OK]

Hint: Always initialize root horizontal distance before traversal [OK]

Common Mistakes:

• Forgetting to set root.hd = 0
• Using Stack instead of Queue for level order
• Assuming HashMap order is sorted

5. Given a binary tree where multiple nodes share the same horizontal distance, how can you modify the top view algorithm to print nodes in order from leftmost to rightmost horizontal distance?

hard

A. Use a TreeMap to store horizontal distances and their nodes

B. Use a HashSet to track visited nodes only

C. Use a Stack to reverse the order of nodes after traversal

D. Use a LinkedList to store nodes in insertion order

Solution

1. Step 1: Understand the need for ordered horizontal distances

   Top view nodes must be printed from leftmost (lowest HD) to rightmost (highest HD). HashMap does not maintain order.

2. Step 2: Use TreeMap for sorted keys

   TreeMap stores keys in sorted order automatically, so storing HD as keys and node data as values allows ordered traversal for printing.

3. Final Answer:

   Use a TreeMap to store horizontal distances and their nodes -> Option A

4. Quick Check:

   TreeMap keeps keys sorted for ordered output [OK]

Hint: Use TreeMap to keep horizontal distances sorted [OK]

Common Mistakes:

• Using HashMap and expecting sorted output
• Trying to reverse order with stack instead of sorting keys
• Ignoring horizontal distance ordering