Binary Tree Longest Consecutive Sequence

To solve this problem, a depth-first search (DFS) approach can be used. When traversing the tree, maintain the current length of consecutive sequence path. If a node’s value is one greater than its parent’s value, then the length of the consecutive path increases by 1, otherwise, it restarts to 1. At each node, the length of the consecutive path is updated, and this value can be compared with the global maximum value to track the longest path.

Here is the solution:

  1. Create a helper function dfs that will be used to traverse the tree.
  2. Initialize a variable max_len to track the maximum length of consecutive sequence path.
  3. For each node, compare its value with its parent’s value to determine the length of the current consecutive path.
  4. Update max_len as needed during the traversal.
  5. Return max_len after the traversal is complete.

Here is the Python code:

# Definition for a binary tree node.
# class TreeNode:
#     def __init__(self, val=0, left=None, right=None):
#         self.val = val
#         self.left = left
#         self.right = right

class Solution:
    def longestConsecutive(self, root: Optional[TreeNode]) -> int:
        # Base case: if the tree is empty, return 0
        if not root:
            return 0

        # Initialize the maximum length to 0
        self.max_len = 0
        def dfs(node, parent, length):
            # Base case: if the node is None, return
            if not node:
            # If the node's value is one greater than its parent's value, increase the length by 1
            if parent and node.val == parent.val + 1:
                length += 1
                length = 1
            # Update the maximum length
            self.max_len = max(self.max_len, length)
            # Continue the DFS traversal on the left and right children
            dfs(node.left, node, length)
            dfs(node.right, node, length)
        # Start the DFS traversal from the root with initial length 0
        dfs(root, None, 0)
        # Return the maximum length found
        return self.max_len

This solution uses DFS to traverse the tree and efficiently finds the longest consecutive sequence path.

Identifying Problem Isomorphism

“Binary Tree Longest Consecutive Sequence” can be approximately mapped to “Longest Increasing Path in a Matrix”.

In both problems, the goal is to find the longest path under certain conditions. In “Binary Tree Longest Consecutive Sequence”, the path should be formed by parent and child nodes with consecutive values, the path can be only in one direction - from parent to child node.

In “Longest Increasing Path in a Matrix”, we’re also looking for the longest increasing sequence, but this time in a 2D matrix rather than a binary tree. The path can be in four directions - up, down, left or right.

The similarity is that they both use depth-first search (DFS) to explore all possible paths and dynamic programming to avoid redundant computations. But, the context (tree vs matrix) and the movement rules (one direction vs four directions) are different, which is why it’s an approximate mapping.

“Longest Increasing Path in a Matrix” is more complex due to the fact that the path can move in four directions as opposed to a single direction in a binary tree, and the need to manage a 2D dynamic programming array.

10 Prerequisite LeetCode Problems

For this, the following are a good preparation:

  1. “104. Maximum Depth of Binary Tree”: This problem helps you understand how to traverse a tree and compute its maximum depth, a useful skill for the main problem where you need to find the longest consecutive sequence path.

  2. “144. Binary Tree Preorder Traversal”: This problem involves the preorder traversal of a binary tree which can be helpful in visiting all nodes in a certain order.

  3. “94. Binary Tree Inorder Traversal”: This problem is about in-order traversal of the binary tree which can help with understanding tree traversal strategies.

  4. “102. Binary Tree Level Order Traversal”: This problem could provide a better understanding of how to traverse each level of a binary tree which is crucial for identifying sequences.

  5. “543. Diameter of Binary Tree”: This problem helps you understand how to calculate the longest path in a binary tree, a crucial concept in the main problem.

  6. “145. Binary Tree Postorder Traversal”: This problem further enhances the understanding of tree traversal by visiting the nodes in post-order.

  7. “687. Longest Univalue Path”: This problem also deals with finding the longest path in a binary tree but under different conditions, so it can be good preparation for the main problem.

  8. “337. House Robber III”: This problem involves traversing a binary tree with certain constraints, similar to the main problem.

  9. “257. Binary Tree Paths”: This problem is about finding all root-to-leaf paths in a binary tree which can help understand how to track and analyze different paths in a binary tree.

  10. “199. Binary Tree Right Side View”: This problem is about visualizing a binary tree from the right side. It can provide practice on thinking about trees in terms of their structural properties.

These cover trees, tree traversal, and analyzing properties of paths within the tree, which are needed to tackle the main problem.

Problem Classification

Problem Statement:Given the root of a binary tree, return the length of the longest consecutive sequence path. A consecutive sequence path is a path where the values increase by one along the path. Note that the path can start at any node in the tree, and you cannot go from a node to its parent in the path.

Example 1:

Input: root = [1,null,3,2,4,null,null,null,5] Output: 3 Explanation: Longest consecutive sequence path is 3-4-5, so return 3.

Example 2:

Input: root = [2,null,3,2,null,1] Output: 2 Explanation: Longest consecutive sequence path is 2-3, not 3-2-1, so return 2.


The number of nodes in the tree is in the range [1, 3 * 104]. -3 * 104 <= Node.val <= 3 * 104

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.

Clarification Questions

What are the clarification questions we can ask about this problem?

Problem Analysis and Key Insights

What are the key insights from analyzing the problem statement?

Problem Boundary

What is the scope of this problem?

How to establish the boundary of this problem?

Distilling the Problem to Its Core Elements

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?

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?


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?


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 edge cases?

How to visualize 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?

Simple Explanation

Can you explain this problem in simple terms or like you would explain to a non-technical person? Imagine you’re explaining this problem to someone without a background in programming. How would you describe it? If you had to explain this problem to a child or someone who doesn’t know anything about coding, how would you do it? In layman’s terms, how would you explain the concept of this problem? Could you provide a metaphor or everyday example to explain the idea of this problem?

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

Can you identify the key terms or concepts in this problem and explain how they inform your approach to solving it? Please list each keyword and how it guides you towards using a specific strategy or method. How can I recognize these properties by drawing tables or diagrams?

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

Simple Explanation of the Proof

I’m having trouble understanding the proof of this algorithm. Could you explain it in a way that’s easy to understand?

Stepwise Refinement

  1. Could you please provide a stepwise refinement of our approach to solving this problem?

  2. How can we take the high-level solution approach and distill it into more granular, actionable steps?

  3. Could you identify any parts of the problem that can be solved independently?

  4. Are there any repeatable patterns within our solution?

Solution Approach and Analysis

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.

Identify Invariant

What is the invariant in this problem?

Identify Loop Invariant

What is the loop invariant in this problem?

Is invariant and loop invariant the same for this problem?

Thought Process

Can you explain the basic thought process and steps involved in solving this type of problem?

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.

Establishing Preconditions and Postconditions

  1. Parameters:

    • What are the inputs to the method?
    • What types are these parameters?
    • What do these parameters represent in the context of the problem?
  2. Preconditions:

    • Before this method is called, what must be true about the state of the program or the values of the parameters?
    • Are there any constraints on the input parameters?
    • Is there a specific state that the program or some part of it must be in?
  3. Method Functionality:

    • What is this method expected to do?
    • How does it interact with the inputs and the current state of the program?
  4. Postconditions:

    • After the method has been called and has returned, what is now true about the state of the program or the values of the parameters?
    • What does the return value represent or indicate?
    • What side effects, if any, does the method have?
  5. Error Handling:

    • How does the method respond if the preconditions are not met?
    • Does it throw an exception, return a special value, or do something else?

Problem Decomposition

  1. Problem Understanding:

    • Can you explain the problem in your own words? What are the key components and requirements?
  2. Initial Breakdown:

    • Start by identifying the major parts or stages of the problem. How can you break the problem into several broad subproblems?
  3. Subproblem Refinement:

    • For each subproblem identified, ask yourself if it can be further broken down. What are the smaller tasks that need to be done to solve each subproblem?
  4. Task Identification:

    • Within these smaller tasks, are there any that are repeated or very similar? Could these be generalized into a single, reusable task?
  5. Task Abstraction:

    • For each task you’ve identified, is it abstracted enough to be clear and reusable, but still makes sense in the context of the problem?
  6. Method Naming:

    • Can you give each task a simple, descriptive name that makes its purpose clear?
  7. Subproblem Interactions:

    • How do these subproblems or tasks interact with each other? In what order do they need to be performed? Are there any dependencies?

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

  1. Identify the initial parameters and explain their significance in the context of the problem statement or the solution domain.

  2. 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?

  3. 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.

  4. 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?

  5. Describe any invariant that’s maintained throughout the code, and explain how it helps meet the problem’s constraints or objectives.

  6. 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 code for the solution of this problem.

  1. What are the high-level problem-solving strategies or techniques being used by this code?

  2. If you had to explain the purpose of this code to a non-programmer, what would you say?

  3. Can you identify the logical elements or constructs used in this code, independent of any programming language?

  4. Could you describe the algorithmic approach used by this code in plain English?

  5. What are the key steps or operations this code is performing on the input data, and why?

  6. 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.

  1. 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.

  2. 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.

  3. 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.

  1. 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.

  2. 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.

  3. 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.


Similar Problems

Can you suggest 10 problems from LeetCode that require similar problem-solving strategies or use similar underlying concepts as the problem we’ve just solved? These problems can be from any domain or topic, but they should involve similar steps or techniques in the solution process. Also, please briefly explain why you consider each of these problems to be related to our original problem. The response text is of the following format:

Here are 10 problems that use similar underlying concepts: