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

Recall & Review

beginner

What is the diameter of a tree?

The diameter of a tree is the longest path between any two nodes in the tree. This path may or may not pass through the root.

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 computing the diameter.

beginner

In the DP approach for 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 in its subtree.

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 two tallest subtrees, representing a path 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, because each node is visited once during the DFS traversal.

What does the diameter of a tree represent?

A Height of the tree

B Shortest path between root and leaf

C Number of nodes in the tree

D Longest path between any two nodes

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

In DP for tree diameter, what is stored at each node during traversal?

A Longest path from node to leaf (height)

B Number of children

C Sum of all node values

D Depth from root

We store the height (longest path from node to leaf) to compute diameter efficiently.

Why do we add the two largest heights of children nodes to update diameter?

A To find the shortest path

B To count total nodes

C To find the longest path passing through the current node

D To calculate the tree's depth

The longest path through a node is the sum of the two largest heights of its children.

What traversal method is commonly used to compute diameter with DP?

A Breadth-First Search (BFS)

B Depth-First Search (DFS)

C Level Order Traversal

D Inorder Traversal

DFS is used to explore nodes and compute heights bottom-up.

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

A O(N)

B O(N^2)

C O(log N)

D O(1)

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 to find longest paths from children and combine them.

Describe the steps to compute the diameter of a tree using a bottom-up approach.

Focus on how information flows from leaves to root.

Practice

1. What does the diameter of a tree represent in graph theory?

easy

A. The number of leaf nodes in the tree

B. The number of nodes in the tree

C. The height of the tree from the root

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

Solution

1. Step 1: Understand the diameter definition

   The diameter is the longest path between any two nodes in a tree, not just from the root.

2. Step 2: Differentiate from other tree properties

   Height is the longest path from root to leaf, number of nodes and leaves are counts, not paths.

3. Final Answer:

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

4. Quick Check:

   Diameter = Longest path [OK]

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

Common Mistakes:

• Confusing diameter with height
• Thinking diameter counts nodes instead of path length
• Assuming diameter is from root only

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

easy

A. ArrayList[] tree = new ArrayList[n];

B. List<Integer>[] tree = new ArrayList[n]; for(int i=0; i();

C. List<Integer> tree = new List[n];

D. ArrayList<Integer> tree = new ArrayList<>(n);

Solution

1. Step 1: Understand adjacency list initialization

   We need an array of lists, each initialized to an empty ArrayList to hold neighbors.

2. Step 2: Check each option

   List<Integer>[] tree = new ArrayList[n]; for(int i=0; i(); correctly creates an array of lists and initializes each element. Others either lack initialization or use wrong types.

3. Final Answer:

   List<Integer>[] tree = new ArrayList[n]; for(int i=0; i -> Option B

4. Quick Check:

   Array of lists with initialization [OK]

Hint: Initialize each list in array separately [OK]

Common Mistakes:

• Not initializing each list element
• Using raw List without generics
• Wrong array type declaration

3. Consider the following Java method to find the diameter of a tree. What will be the output if the tree edges are: 0-1, 1-2, 1-3?

int diameter = 0;
int dfs(int node, int parent, List<Integer>[] tree) {
  int max1 = 0, max2 = 0;
  for (int child : tree[node]) {
    if (child == parent) continue;
    int height = dfs(child, node, tree) + 1;
    if (height > max1) {
      max2 = max1;
      max1 = height;
    } else if (height > max2) {
      max2 = height;
    }
  }
  diameter = Math.max(diameter, max1 + max2);
  return max1;
}
// call dfs(0, -1, tree) and then print diameter;

medium

A. 2

B. 3

C. 1

D. 0

Solution

1. Step 1: Build the tree and understand paths

   The tree edges are 0-1, 1-2, 1-3. The longest path is from node 2 to node 0 or 3 to 0, length 2 edges.

2. Step 2: Trace DFS and diameter calculation

   DFS calculates max heights from children and updates diameter as sum of two largest heights. Here, diameter becomes 2.

3. Final Answer:

   2 -> Option A

4. Quick Check:

   Longest path length = 2 edges [OK]

Hint: Diameter = sum of two largest subtree heights [OK]

Common Mistakes:

• Counting nodes instead of edges
• Ignoring parent check in DFS
• Miscomputing max heights

4. The following code attempts to compute the diameter of a tree but has a bug. What is the bug?

int diameter = 0;
int dfs(int node, int parent, List<Integer>[] tree) {
  int max1 = 0, max2 = 0;
  for (int child : tree[node]) {
    int height = dfs(child, node, tree) + 1;
    if (height > max1) {
      max2 = max1;
      max1 = height;
    } else if (height > max2) {
      max2 = height;
    }
  }
  diameter = Math.max(diameter, max1 + max2);
  return max1;
}
// call dfs(0, -1, tree);

medium

A. Missing check to skip parent node in DFS

B. Incorrect update of diameter variable

C. Wrong return value from DFS

D. Initialization of max1 and max2 is incorrect

Solution

1. Step 1: Analyze DFS loop over children

   The code calls dfs on all children but does not skip the parent node, causing infinite recursion or stack overflow.

2. Step 2: Identify missing condition

   There should be a condition to continue if child == parent to avoid revisiting the parent.

3. Final Answer:

   Missing check to skip parent node in DFS -> Option A

4. Quick Check:

   Skip parent to prevent infinite recursion [OK]

Hint: Always skip parent node in tree DFS [OK]

Common Mistakes:

• Forgetting to skip parent node
• Misplacing diameter update
• Returning wrong height

5. You want to find the diameter of a weighted tree where edges have positive weights. Which modification to the standard diameter DFS approach is correct?

hard

A. Use BFS twice without considering weights

B. Ignore weights and count edges as 1 each

C. Add edge weights to the height calculation instead of just adding 1

D. Calculate diameter by summing all edge weights in the tree

Solution

1. Step 1: Understand weighted tree diameter

   In weighted trees, path length is sum of edge weights, not just number of edges.

2. Step 2: Modify DFS height calculation

   Instead of adding 1 for each edge, add the actual edge weight to the height returned by DFS.

3. Step 3: Update diameter similarly

   Diameter is max sum of two largest weighted heights from children.

4. Final Answer:

   Add edge weights to the height calculation instead of just adding 1 -> Option C

5. Quick Check:

   Use weights in height sums for weighted diameter [OK]

Hint: Add edge weights, not just count edges [OK]

Common Mistakes:

• Ignoring weights in diameter calculation
• Using BFS without weights
• Summing all edges instead of longest path