DP on Trees Diameter of Tree in DSA C# - Time & Space Complexity

Time Complexity: DP on Trees Diameter of Tree

O(n)

Understanding Time Complexity

We want to understand how long it takes to find the diameter of a tree using dynamic programming.

The question is: how does the time grow as the tree gets bigger?

Scenario Under Consideration

Analyze the time complexity of the following code snippet.

// Tree represented as adjacency list
List<int>[] tree = new List<int>[n];
int diameter = 0;

int DFS(int node, int parent) {
    int max1 = 0, max2 = 0;
    foreach (var child in tree[node]) {
        if (child == parent) continue;
        int height = DFS(child, node) + 1;
        if (height > max1) { max2 = max1; max1 = height; }
        else if (height > max2) max2 = height;
    }
    diameter = Math.Max(diameter, max1 + max2);
    return max1;
}

DFS(0, -1); // start DFS from root

This code finds the diameter of a tree by exploring each node once and tracking the longest paths.

Identify Repeating Operations

Identify the loops, recursion, array traversals that repeat.

• Primary operation: DFS visits each node once and explores its children.
• How many times: Each node and edge is visited exactly once during the DFS traversal.

How Execution Grows With Input

As the number of nodes grows, the DFS explores each node and its edges once.

Input Size (n)	Approx. Operations
10	About 10 nodes + 9 edges = 19 visits
100	About 100 nodes + 99 edges = 199 visits
1000	About 1000 nodes + 999 edges = 1999 visits

Pattern observation: The operations grow roughly in a straight line with the number of nodes.

Final Time Complexity

Time Complexity: O(n)

This means the time to find the diameter grows linearly with the number of nodes in the tree.

Common Mistake

[X] Wrong: "Since we check children inside a loop, the time is O(n²)."

[OK] Correct: Each edge and node is visited only once in total, so the total work is linear, not quadratic.

Interview Connect

Understanding this linear time DFS approach is a key skill for tree problems and shows you can handle recursion and dynamic programming on trees efficiently.

Self-Check

"What if the tree was stored as an edge list without adjacency lists? How would that affect the time complexity?"

Practice

1. What does the diameter of a tree represent in the context of DP on Trees?

easy

A. The height of the tree from the root

B. The longest path between any two nodes in the tree

C. The number of nodes in the tree

D. The total sum of all node values

Solution

1. Step 1: Understand the definition of tree diameter

   The diameter is the longest path between any two nodes in a tree, not necessarily passing through the root.

2. Step 2: Differentiate diameter from other tree properties

   Height is the longest path from root to leaf, number of nodes is size, and sum of values is unrelated to diameter.

3. Final Answer:

   The longest path between any two nodes in the tree -> Option B

4. Quick Check:

   Diameter = longest path [OK]

Hint: Diameter is longest path between any two nodes [OK]

Common Mistakes:

• Confusing diameter with height
• Thinking diameter is number of nodes
• Assuming diameter passes through root

2. Which of the following C# code snippets correctly initializes an adjacency list for a tree with n nodes?

easy

A. var graph = new List<int>[n]; for(int i=0; i

B. var graph = new List<int>(n); for(int i=0; i

C. var graph = new List(); for(int i=0; i

D. var graph = new List<int>[n]; graph = new List<int>();

Solution

1. Step 1: Understand adjacency list initialization in C#

   For n nodes, create an array of List<int> with size n, then initialize each element with new List<int>().

2. Step 2: Analyze each option

   A: var graph = new List<int>[n]; for(int i=0; i(); for(int i=0; i

3. Final Answer:

   var graph = new List<int>[n]; for(int i=0; i -> Option A

4. Quick Check:

   Array of lists initialized correctly [OK]

Hint: Use array of lists and initialize each element [OK]

Common Mistakes:

• Not initializing each list element
• Using List<int> without specifying size
• Overwriting array with a single list

3. Consider the following C# code snippet to compute the diameter of a tree. What will be the output printed?

using System;
using System.Collections.Generic;

class Program {
    static List<int>[] graph;
    static int diameter = 0;

    static int DFS(int node, int parent) {
        int max1 = 0, max2 = 0;
        foreach (var child in graph[node]) {
            if (child == parent) continue;
            int dist = DFS(child, node) + 1;
            if (dist > max1) {
                max2 = max1;
                max1 = dist;
            } else if (dist > max2) {
                max2 = dist;
            }
        }
        diameter = Math.Max(diameter, max1 + max2);
        return max1;
    }

    static void Main() {
        int n = 5;
        graph = new List<int>[n];
        for (int i = 0; i < n; i++) graph[i] = new List<int>();
        graph[0].Add(1); graph[1].Add(0);
        graph[1].Add(2); graph[2].Add(1);
        graph[1].Add(3); graph[3].Add(1);
        graph[3].Add(4); graph[4].Add(3);

        DFS(0, -1);
        Console.WriteLine(diameter);
    }
}

medium

A. 2

B. 5

C. 3

D. 4

Solution

1. Step 1: Understand the tree structure and DFS traversal

   The tree edges are: 0-1, 1-2, 1-3, 3-4. The longest path is from node 2 to node 4 passing through 1 and 3, length 3 edges.

2. Step 2: Trace DFS and diameter calculation

   DFS calculates max distances from each node's children. Diameter updates to max sum of two longest child paths. The longest path length is 3.

3. Final Answer:

   3 -> Option C

4. Quick Check:

   Longest path length = 3 edges [OK]

Hint: Diameter = longest path edges between two nodes [OK]

Common Mistakes:

• Counting nodes instead of edges
• Misunderstanding DFS return values
• Ignoring parent check in DFS

4. The following code attempts to compute the diameter of a tree but produces incorrect results. What is the main bug?

static int DFS(int node, int parent) {
    int maxDist = 0;
    foreach (var child in graph[node]) {
        if (child == parent) continue;
        int dist = DFS(child, node) + 1;
        if (dist > maxDist) maxDist = dist;
    }
    diameter = Math.Max(diameter, maxDist);
    return maxDist;
}

medium

A. It does not check for parent node, causing infinite recursion

B. It updates diameter inside the loop incorrectly

C. It returns distance without adding 1 for edge

D. It only considers the longest single path, missing combined paths for diameter

Solution

1. Step 1: Analyze how diameter is updated

   The code tracks only the longest single path from children, ignoring the sum of two longest paths needed for diameter.

2. Step 2: Understand diameter definition

   Diameter is the longest path between any two nodes, which may be sum of two longest child paths through current node, not just one.

3. Final Answer:

   It only considers the longest single path, missing combined paths for diameter -> Option D

4. Quick Check:

   Diameter needs sum of two longest paths [OK]

Hint: Diameter = sum of two longest child paths, not just one [OK]

Common Mistakes:

• Ignoring second longest path
• Forgetting to skip parent node
• Updating diameter inside loop incorrectly

5. Given a weighted tree where edges have positive weights, how would you modify the DP approach to find the diameter of the tree?

hard

A. Replace increments by edge weights when calculating distances in DFS

B. Ignore weights and count edges as 1 each

C. Use BFS instead of DFS without changes

D. Sum all edge weights and divide by number of edges

Solution

1. Step 1: Understand difference between unweighted and weighted trees

   In weighted trees, edge lengths vary, so distance must accumulate actual weights, not just count edges.

2. Step 2: Modify DFS to add edge weights

   Instead of adding 1 for each edge, add the weight of the edge when calculating distances and updating diameter.

3. Step 3: Ignore incorrect options

   Ignoring weights loses accuracy, BFS alone doesn't solve weighted distances, summing all weights is unrelated to diameter.

4. Final Answer:

   Replace increments by edge weights when calculating distances in DFS -> Option A

5. Quick Check:

   Use edge weights in distance sums [OK]

Hint: Add edge weights instead of 1 in DFS distance calculation [OK]

Common Mistakes:

• Counting edges as 1 ignoring weights
• Using BFS without weight handling
• Summing all weights unrelated to diameter