Longest Continuous Subarray With Absolute Diff Less Than or Equal to Limit
The problem is about finding the longest subarray from the given array nums
where the absolute difference between any two elements in the subarray is less than or equal to a given limit
. To achieve this, we can use a deque to efficiently maintain both minimum and maximum values of the current window, thus helping in calculating the difference within the limit
.
Here’s the code:


Explanation:
Initialize Deques and Variables: Use two deques to keep track of the maximum and minimum values of the current window. Initialize variables for the left pointer and maximum length found so far.
Iterate Through the Array: Traverse through the array. For each number, keep the deques sorted by removing the rightmost elements that are smaller (in
max_deque
) or greater (inmin_deque
) than the current number.Add Current Number to Deques: Append the current number to both deques.
Check the Limit Condition: If the difference between the maximum and minimum values exceeds the limit, update the left pointer and remove the corresponding elements from the deques.
Update Maximum Length: For each iteration, update the maximum length if the current window size is greater.
Return Result: Finally, return the maximum length found, which represents the size of the longest subarray satisfying the given condition.
By using deques, we maintain the window’s maximum and minimum values efficiently, allowing us to solve this problem in linear time.
Identifying Problem Isomorphism
“Longest Continuous Subarray With Absolute Diff Less Than or Equal to Limit” is approximately isomorphic to “Sliding Window Maximum”.
Reasoning: Both deal with arrays and require a window of a certain size that meets certain criteria to be identified. In “Longest Continuous Subarray With Absolute Diff Less Than or Equal to Limit”, the goal is to find the longest subarray where the absolute difference between any two elements is less than or equal to the limit. On the other hand, “Sliding Window Maximum” also involves identifying a subarray (window) of a certain size, but the goal here is to calculate the maximum value in the window and then slide it along the array.
Another isomorphic problem is “Maximum Size Subarray Sum Equals k”.
Reasoning: While the context differs, this problem similarly involves identifying a subarray within an array that meets certain criteria. Here, the goal is to find the maximum size subarray that sums to a given number k.
In terms of complexity, from simpler to more complex:
 Maximum Size Subarray Sum Equals k
 Sliding Window Maximum
 Longest Continuous Subarray With Absolute Diff Less Than or Equal to Limit
“Maximum Size Subarray Sum Equals k” is simpler because it merely involves calculating a sum and doesn’t involve comparing differences or maximums. The problem “Sliding Window Maximum” is slightly more complex because it not only involves identifying the maximum within a window but also requires the window to slide along the array. The problem “Longest Continuous Subarray With Absolute Diff Less Than or Equal to Limit” is more complex because it involves finding a maximum size subarray where the absolute difference between any two elements is less than or equal to a limit, which adds an additional layer of complexity.
10 Prerequisite LeetCode Problems
“Longest Continuous Subarray With Absolute Diff Less Than or Equal to Limit” is based on the sliding window technique and use of data structures such as deque (doubleended queue). Here are 10 problems to build the necessary skills:
LeetCode 3: Longest Substring Without Repeating Characters
 This problem helps you understand the basic concept of sliding window.
LeetCode 209: Minimum Size Subarray Sum
 This problem provides practice on sliding window with a twist of finding the minimum subarray sum.
LeetCode 76: Minimum Window Substring
 This problem is another variant of the sliding window technique where you have to find a substring.
LeetCode 438: Find All Anagrams in a String
 This problem uses a sliding window to examine all possible anagrams of a string within another string.
LeetCode 239: Sliding Window Maximum
 This problem will help you understand how to maintain a deque (doubleended queue) in a sliding window problem.
LeetCode 485: Max Consecutive Ones
 This problem helps you understand how to handle binary array problems using a sliding window.
LeetCode 1004: Max Consecutive Ones III
 This problem takes it a step further by allowing the flipping of K zeros in a binary array.
LeetCode 567: Permutation in String
 This problem uses the sliding window technique with a check for permutation of a string.
LeetCode 424: Longest Repeating Character Replacement
 This problem requires maintaining a sliding window that can contain a string with k changes allowed.
LeetCode 340: Longest Substring with At Most K Distinct Characters
 This problem requires maintaining a sliding window with at most K distinct characters, building upon the concept of character counts and sliding windows.
These cover how to manipulate the sliding window according to the problem’s needs and use a deque efficiently. These skills are essential for solving problem 1438.
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?
Problem Classification
Problem Statement:Given an array of integers nums and an integer limit, return the size of the longest nonempty subarray such that the absolute difference between any two elements of this subarray is less than or equal to limit.
Example 1:
Input: nums = [8,2,4,7], limit = 4 Output: 2 Explanation: All subarrays are: [8] with maximum absolute diff 88 = 0 <= 4. [8,2] with maximum absolute diff 82 = 6 > 4. [8,2,4] with maximum absolute diff 82 = 6 > 4. [8,2,4,7] with maximum absolute diff 82 = 6 > 4. [2] with maximum absolute diff 22 = 0 <= 4. [2,4] with maximum absolute diff 24 = 2 <= 4. [2,4,7] with maximum absolute diff 27 = 5 > 4. [4] with maximum absolute diff 44 = 0 <= 4. [4,7] with maximum absolute diff 47 = 3 <= 4. [7] with maximum absolute diff 77 = 0 <= 4. Therefore, the size of the longest subarray is 2.
Example 2:
Input: nums = [10,1,2,4,7,2], limit = 5 Output: 4 Explanation: The subarray [2,4,7,2] is the longest since the maximum absolute diff is 27 = 5 <= 5. Example 3:
Input: nums = [4,2,2,2,4,4,2,2], limit = 0 Output: 3
Constraints:
1 <= nums.length <= 105 1 <= nums[i] <= 109 0 <= limit <= 109
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
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 realworld 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 edge 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 nontechnical 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 ProblemSolving 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
Could you please provide a stepwise refinement of our approach to solving this problem?
How can we take the highlevel 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
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?
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
Parameters:
 What are the inputs to the method?
 What types are these parameters?
 What do these parameters represent in the context of the problem?
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?
Method Functionality:
 What is this method expected to do?
 How does it interact with the inputs and the current state of the program?
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?
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
Problem Understanding:
 Can you explain the problem in your own words? What are the key components and requirements?
Initial Breakdown:
 Start by identifying the major parts or stages of the problem. How can you break the problem into several broad subproblems?
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?
Task Identification:
 Within these smaller tasks, are there any that are repeated or very similar? Could these be generalized into a single, reusable task?
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?
Method Naming:
 Can you give each task a simple, descriptive name that makes its purpose clear?
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
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 highlevel problemsolving strategies or techniques being used by this code?
If you had to explain the purpose of this code to a nonprogrammer, 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 languageagnostic 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 problemsolving 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 stepbystep 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 Pythonbased 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 problemspecific 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.
Q&A
Similar Problems
Can you suggest 10 problems from LeetCode that require similar problemsolving 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.