DP on Trees Diameter of Tree in DSA C# - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the diameter of a tree?

The diameter of a tree is the length of the longest path between any two nodes in the tree.

intermediate

How can dynamic programming help in finding the diameter of a tree?

Dynamic programming helps by storing the longest path from each node to its descendants, avoiding repeated calculations and efficiently finding the diameter.

beginner

In the context of tree diameter, what does the 'height' of a node represent?

The height of a node is the length of the longest path from that node down to a leaf node.

intermediate

Why do we consider the sum of the two largest heights of children nodes when computing the diameter?

Because the longest path through a node can be formed by joining the two longest paths from its children, passing through that node.

intermediate

What is the time complexity of finding the diameter of a tree using DP?

The time complexity is O(N), where N is the number of nodes, since each node is visited once during the DFS traversal.

What does the diameter of a tree represent?

A The longest path between any two nodes

B The number of nodes in the tree

C The height of the root node

D The shortest path between two leaves

The diameter is the longest path between any two nodes in the tree.

Which technique helps avoid repeated calculations when finding the diameter?

A Greedy Algorithm

B Sorting

C Brute Force

D Dynamic Programming

Dynamic Programming stores intermediate results to avoid repeated work.

When calculating diameter, why do we consider two largest heights from children?

A To find the longest path passing through the current node

B To calculate the total number of children

C To find the shortest path

D To balance the tree

The longest path through a node can be formed by joining the two longest child paths.

What is the height of a leaf node?

A Depends on the tree

B 0

C 1

D Undefined

A leaf node has height 0 because it has no children.

What is the time complexity of the DP approach to find tree diameter?

A O(1)

B O(N^2)

C O(N)

D O(log N)

Each node is visited once, so the complexity is linear in the number of nodes.

Explain how dynamic programming is used to find the diameter of a tree.

Think about how you can use information from children nodes to find the longest path.

Describe the steps to compute the diameter of a tree using a depth-first search.

Focus on what information each node returns to its parent.

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