Height of Binary Tree After Subtree Removal Queries

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class Solution:
    def treeQueries(self, root: TreeNode, queries: List[int]) -> List[int]:
        preh = [0] * 100001
        posth = [0] * 100001
        maxh = 0

        def pre(root, h):
            nonlocal maxh
            if not root:
                return
            preh[root.val] = maxh
            maxh = max(maxh, h)
            pre(root.left, h + 1)
            pre(root.right, h + 1)

        def post(root, h):
            nonlocal maxh
            if not root:
                return
            posth[root.val] = maxh
            maxh = max(maxh, h)
            post(root.right, h + 1)
            post(root.left, h + 1)

        maxh = 0
        pre(root, 0)
        maxh = 0
        post(root, 0)

        res = []
        for q in queries:
            res.append(max(preh[q], posth[q]))

        return res

Identifying Problem Isomorphism

“Height of Binary Tree After Subtree Removal Queries” has an approximate isomorphism “All Nodes Distance K in Binary Tree”. Both problems involve working with binary trees and making alterations based on certain conditions, then returning specific results.

In “Height of Binary Tree After Subtree Removal Queries”, you’re given a binary tree and an array of nodes to be deleted. After each deletion, you need to return the height of the tree.

In “All Nodes Distance K in Binary Tree”, you’re given a binary tree, a target node, and an integer value K. You need to return a list of the values of all nodes that have a distance K from the target node.

Both share the common theme of working with binary trees and performing specific actions based on the nodes in the tree. However, they are different in their objectives and the actions that need to be performed.

“Height of Binary Tree After Subtree Removal Queries” is the more complex problem due to the need to keep track of tree heights after each node deletion, which would involve tree traversal and potentially rebalancing the tree. “All Nodes Distance K in Binary Tree”, on the other hand, is simpler as it only requires tree traversal to find nodes at a certain distance from the target node.

10 Prerequisite LeetCode Problems

“2458. Height of Binary Tree After Subtree Removal Queries” involves binary trees, depth calculation, and handling queries to remove subtrees. Below are 10 problems as a preparation for this problem:

“104. Maximum Depth of Binary Tree”: This problem involves finding the maximum depth (or height) of a binary tree. Understanding this would be key to determining the height after subtree removal.
“110. Balanced Binary Tree”: In this problem, you need to determine if a binary tree is height-balanced. This would enhance your understanding of tree heights.
“111. Minimum Depth of Binary Tree”: This problem is similar to problem 104 but asks for the minimum depth instead. It’s another way to practice depth calculation.
“112. Path Sum”: This problem involves determining if the tree has a root-to-leaf path such that adding up all the values along the path equals a given sum. It introduces the concept of tree paths.
“114. Flatten Binary Tree to Linked List”: This problem asks you to flatten a binary tree into a linked list, which may be helpful in visualizing tree structures.
“450. Delete Node in a BST”: In this problem, you need to delete a node from a BST. Understanding node deletion would be key in removing subtrees.
“617. Merge Two Binary Trees”: This problem involves merging two binary trees. This might help you understand the tree structure better and learn how to manipulate it.
“669. Trim a Binary Search Tree”: This problem asks you to trim the BST such that all its elements lies in a given range. It will help you in understanding how to remove nodes from the tree.
“701. Insert into a Binary Search Tree”: This problem involves adding a new node into a BST. This, along with the deletion problem, would give you a comprehensive understanding of BST manipulation.
“814. Binary Tree Pruning”: This problem involves pruning a binary tree based on a specific rule. It will help you in understanding how to modify a tree based on certain conditions.

These cover binary trees and manipulating their structure, which is beneficial in solving the problem “2458. Height of Binary Tree After Subtree Removal Queries”.

Problem Classification

Problem Statement: You are given the root of a binary tree with n nodes. Each node is assigned a unique value from 1 to n. You are also given an array queries of size m.

You have to perform m independent queries on the tree where in the ith query you do the following:

Remove the subtree rooted at the node with the value queries[i] from the tree. It is guaranteed that queries[i] will not be equal to the value of the root. Return an array answer of size m where answer[i] is the height of the tree after performing the ith query.

Note:

The queries are independent, so the tree returns to its initial state after each query. The height of a tree is the number of edges in the longest simple path from the root to some node in the tree.

Example 1:

Input: root = [1,3,4,2,null,6,5,null,null,null,null,null,7], queries = [4] Output: [2] Explanation: The diagram above shows the tree after removing the subtree rooted at node with value 4. The height of the tree is 2 (The path 1 -> 3 -> 2).

Example 2:

Input: root = [5,8,9,2,1,3,7,4,6], queries = [3,2,4,8] Output: [3,2,3,2] Explanation: We have the following queries:

Removing the subtree rooted at node with value 3. The height of the tree becomes 3 (The path 5 -> 8 -> 2 -> 4).
Removing the subtree rooted at node with value 2. The height of the tree becomes 2 (The path 5 -> 8 -> 1).
Removing the subtree rooted at node with value 4. The height of the tree becomes 3 (The path 5 -> 8 -> 2 -> 6).
Removing the subtree rooted at node with value 8. The height of the tree becomes 2 (The path 5 -> 9 -> 3).

Constraints:

The number of nodes in the tree is n. 2 <= n <= 105 1 <= Node.val <= n All the values in the tree are unique. m == queries.length 1 <= m <= min(n, 104) 1 <= queries[i] <= n queries[i] != root.val

Analyze the provided problem statement. Categorize it based on its domain, ignoring ‘How’ it might be solved. Identify and list out the ‘What’ components. Based on these, further classify the problem. Explain your categorizations.

Distilling the Problem to Its Core Elements

In order to have me distill a problem to its core, you could ask questions that prompt for a deeper analysis of the problem, understanding of the underlying concepts, and simplification of the problem’s essence. Here are some examples of such prompts:

Can you identify the fundamental concept or principle this problem is based upon? Please explain.
What is the simplest way you would describe this problem to someone unfamiliar with the subject?
What is the core problem we are trying to solve? Can we simplify the problem statement?
Can you break down the problem into its key components?
What is the minimal set of operations we need to perform to solve this problem?

These prompts guide the discussion towards simplifying the problem, stripping it down to its essential elements, and understanding the core problem to be solved.

Visual Model of the Problem

How to visualize the problem statement for this problem?

Problem Restatement

Could you start by paraphrasing the problem statement in your own words? Try to distill the problem into its essential elements and make sure to clarify the requirements and constraints. This exercise should aid in understanding the problem better and aligning our thought process before jumping into solving it.

Abstract Representation of the Problem

Could you help me formulate an abstract representation of this problem?

Given this problem, how can we describe it in an abstract way that emphasizes the structure and key elements, without the specific real-world details?

Terminology

Are there any specialized terms, jargon, or technical concepts that are crucial to understanding this problem or solution? Could you define them and explain their role within the context of this problem?

Problem Simplification and Explanation

Could you please break down this problem into simpler terms? What are the key concepts involved and how do they interact? Can you also provide a metaphor or analogy to help me understand the problem better?

Constraints

Given the problem statement and the constraints provided, identify specific characteristics or conditions that can be exploited to our advantage in finding an efficient solution. Look for patterns or specific numerical ranges that could be useful in manipulating or interpreting the data.

What are the key insights from analyzing the constraints?

Case Analysis

Could you please provide additional examples or test cases that cover a wider range of the input space, including edge and boundary conditions? In doing so, could you also analyze each example to highlight different aspects of the problem, key constraints and potential pitfalls, as well as the reasoning behind the expected output for each case? This should help in generating key insights about the problem and ensuring the solution is robust and handles all possible scenarios.

Provide names by categorizing these cases

What are the key insights from analyzing the different cases?

Identification of Applicable Theoretical Concepts

Can you identify any mathematical or algorithmic concepts or properties that can be applied to simplify the problem or make it more manageable? Think about the nature of the operations or manipulations required by the problem statement. Are there existing theories, metrics, or methodologies in mathematics, computer science, or related fields that can be applied to calculate, measure, or perform these operations more effectively or efficiently?

Problem Breakdown and Solution Methodology

Given the problem statement, can you explain in detail how you would approach solving it? Please break down the process into smaller steps, illustrating how each step contributes to the overall solution. If applicable, consider using metaphors, analogies, or visual representations to make your explanation more intuitive. After explaining the process, can you also discuss how specific operations or changes in the problem’s parameters would affect the solution? Lastly, demonstrate the workings of your approach using one or more example cases.

Inference of Problem-Solving Approach from the Problem Statement

How did you infer from the problem statement that this problem can be solved using ?

Could you please provide a stepwise refinement of our approach to solving this problem?
How can we take the high-level solution approach and distill it into more granular, actionable steps?
Could you identify any parts of the problem that can be solved independently?
Are there any repeatable patterns within our solution?

Solution Approach and Analysis

Thought Process

Explain the thought process by thinking step by step to solve this problem from the problem statement and code the final solution. Write code in Python3. What are the cues in the problem statement? What direction does it suggest in the approach to the problem? Generate insights about the problem statement.

From Brute Force to Optimal Solution

Could you please begin by illustrating a brute force solution for this problem? After detailing and discussing the inefficiencies of the brute force approach, could you then guide us through the process of optimizing this solution? Please explain each step towards optimization, discussing the reasoning behind each decision made, and how it improves upon the previous solution. Also, could you show how these optimizations impact the time and space complexity of our solution?

Code Explanation and Design Decisions

Identify the initial parameters and explain their significance in the context of the problem statement or the solution domain.
Discuss the primary loop or iteration over the input data. What does each iteration represent in terms of the problem you’re trying to solve? How does the iteration advance or contribute to the solution?
If there are conditions or branches within the loop, what do these conditions signify? Explain the logical reasoning behind the branching in the context of the problem’s constraints or requirements.
If there are updates or modifications to parameters within the loop, clarify why these changes are necessary. How do these modifications reflect changes in the state of the solution or the constraints of the problem?
Describe any invariant that’s maintained throughout the code, and explain how it helps meet the problem’s constraints or objectives.
Discuss the significance of the final output in relation to the problem statement or solution domain. What does it represent and how does it satisfy the problem’s requirements?

Remember, the focus here is not to explain what the code does on a syntactic level, but to communicate the intent and rationale behind the code in the context of the problem being solved.

Coding Constructs

Consider the following piece of complex software code.

What are the high-level problem-solving strategies or techniques being used by this code?
If you had to explain the purpose of this code to a non-programmer, what would you say?
Can you identify the logical elements or constructs used in this code, independent of any programming language?
Could you describe the algorithmic approach used by this code in plain English?
What are the key steps or operations this code is performing on the input data, and why?
Can you identify the algorithmic patterns or strategies used by this code, irrespective of the specific programming language syntax?

Language Agnostic Coding Drills

Your mission is to deconstruct this code into the smallest possible learning units, each corresponding to a separate coding concept. Consider these concepts as unique coding drills that can be individually implemented and later assembled into the final solution.

Dissect the code and identify each distinct concept it contains. Remember, this process should be language-agnostic and generally applicable to most modern programming languages.
Once you’ve identified these coding concepts or drills, list them out in order of increasing difficulty. Provide a brief description of each concept and why it is classified at its particular difficulty level.
Next, describe the problem-solving approach that would lead from the problem statement to the final solution. Think about how each of these coding drills contributes to the overall solution. Elucidate the step-by-step process involved in using these drills to solve the problem. Please refrain from writing any actual code; we’re focusing on understanding the process and strategy.

Targeted Drills in Python

Now that you’ve identified and ordered the coding concepts from a complex software code in the previous exercise, let’s focus on creating Python-based coding drills for each of those concepts.

Begin by writing a separate piece of Python code that encapsulates each identified concept. These individual drills should illustrate how to implement each concept in Python. Please ensure that these are suitable even for those with a basic understanding of Python.
In addition to the general concepts, identify and write coding drills for any problem-specific concepts that might be needed to create a solution. Describe why these drills are essential for our problem.
Once all drills have been coded, describe how these pieces can be integrated together in the right order to solve the initial problem. Each drill should contribute to building up to the final solution.

Remember, the goal is to not only to write these drills but also to ensure that they can be cohesively assembled into one comprehensive solution.