Height and depth of trees in Data Structures Theory - Time & Space Complexity

Time Complexity: Height and depth of trees

O(n)

Understanding Time Complexity

When working with trees, it is important to understand how the height and depth affect the time it takes to perform operations.

We want to know how the number of steps grows as the tree gets bigger.

Scenario Under Consideration

Analyze the time complexity of finding the height of a tree using recursion.

function height(node) {
  if (node == null) return -1;
  let leftHeight = height(node.left);
  let rightHeight = height(node.right);
  return 1 + Math.max(leftHeight, rightHeight);
}
    

This code calculates the height by checking the height of left and right subtrees recursively.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: Recursive calls to visit each node once.
• How many times: Once per node in the tree.

How Execution Grows With Input

As the tree grows, the function visits every node once to find the height.

Input Size (n)	Approx. Operations
10	About 10 visits
100	About 100 visits
1000	About 1000 visits

Pattern observation: The number of steps grows directly with the number of nodes.

Final Time Complexity

Time Complexity: O(n)

This means the time to find the height grows in direct proportion to the number of nodes in the tree.

Common Mistake

[X] Wrong: "The height can be found without visiting all nodes."

[OK] Correct: Because the height depends on the longest path, you must check all nodes to be sure.

Interview Connect

Understanding how tree height and depth affect time helps you explain and reason about tree operations clearly.

Self-Check

"What if the tree is balanced versus very unbalanced? How would that affect the time complexity of finding height?"

Practice

1. What does the depth of a node in a tree represent?

easy

A. The number of edges from the root to that node

B. The number of edges from that node to the farthest leaf

C. The total number of nodes in the tree

D. The number of children the node has

Solution

1. Step 1: Understand the definition of depth

   Depth is defined as the distance from the root node to the given node, measured in edges.

2. Step 2: Compare with other options

   Height measures distance to farthest leaf, not depth. Total nodes and children count are unrelated.

3. Final Answer:

   The number of edges from the root to that node -> Option A

4. Quick Check:

   Depth = edges from root to node [OK]

Hint: Depth counts edges from root down to the node [OK]

Common Mistakes:

• Confusing depth with height
• Thinking depth counts children
• Mixing depth with total nodes

2. Which of the following correctly describes the height of a leaf node in a tree?

easy

A. Height is always 1

B. Height is 0 because it has no children

C. Height equals the depth of the leaf

D. Height is the number of siblings it has

Solution

1. Step 1: Recall height definition for any node

   Height is the number of edges on the longest path from the node down to a leaf.

2. Step 2: Apply to leaf node

   A leaf node has no children, so the longest path down is zero edges, making height 0.

3. Final Answer:

   Height is 0 because it has no children -> Option B

4. Quick Check:

   Leaf height = 0 edges down [OK]

Hint: Leaf nodes always have height zero [OK]

Common Mistakes:

• Assuming height is 1 for leaves
• Confusing height with depth
• Counting siblings as height

3. Consider the following tree structure:

        A
       / \
      B   C
     /   / \
    D   E   F
           /
          G

What is the height of node C?

medium

A. 0

B. 1

C. 3

D. 2

Solution

1. Step 1: Identify the subtree rooted at node C

   Node C has children E and F; F has child G.

2. Step 2: Find longest path from C down to a leaf

   Paths: C->E (1 edge), C->F->G (2 edges). Longest path length is 2 edges.

3. Final Answer:

   2 -> Option D

4. Quick Check:

   Height of C = longest path down = 2 edges [OK]

Hint: Height = longest edges down from node [OK]

Common Mistakes:

• Counting number of children instead of edges
• Confusing height with depth
• Ignoring deeper descendants

4. A student wrote that the depth of the root node in any tree is 1. What is wrong with this statement?

medium

A. Depth depends on number of children, not fixed

B. Depth of root is always equal to height

C. Depth of root is always 0, not 1

D. Depth cannot be defined for root node

Solution

1. Step 1: Recall definition of depth for root

   Depth is edges from root to node; root is at distance zero from itself.

2. Step 2: Identify error in student's statement

   Student incorrectly assigns depth 1 to root; correct depth is 0.

3. Final Answer:

   Depth of root is always 0, not 1 -> Option C

4. Quick Check:

   Root depth = 0 edges [OK]

Hint: Root node depth is zero by definition [OK]

Common Mistakes:

• Assigning depth 1 to root
• Confusing depth with height
• Thinking depth depends on children

5. Given a tree where the root node has depth 0 and height 4, and a node at depth 3 has height 1, what is the height of a leaf node at depth 4?

hard

A. 0

B. 1

C. 3

D. 4

Solution

1. Step 1: Understand height of leaf nodes

   Leaf nodes have height 0 because they have no children below.

2. Step 2: Apply to leaf at depth 4

   Since the node at depth 3 has height 1, its child at depth 4 must be a leaf with height 0.

3. Final Answer:

   0 -> Option A

4. Quick Check:

   Leaf node height = 0 [OK]

Hint: Leaf nodes always have height zero regardless of depth [OK]

Common Mistakes:

• Assuming height equals depth
• Thinking height increases with depth
• Confusing height with number of siblings