The Most Similar Path in a Graph
The problem involves finding a path in the given graph that has the same length and minimum edit distance to the given targetPath
. We can model this problem as a dynamic programming (DP) problem where we maintain a 2D table dp
, where dp[i][j]
will represent the minimum edit distance for the first i
elements of targetPath
when we are at city j
.
We’ll also use a 2D table parent
to store the previous city in the path that leads to the minimum edit distance. This will help in reconstructing the final path.
Here’s how to solve the problem:
 Preprocess the Roads: Create a list of neighbors for each city using the given
roads
.  Initialize the DP Table:
dp[i][j]
will represent the minimum edit distance for the firsti
elements oftargetPath
when we are at cityj
. Initializedp[0][j] = 0
for allj
.  Dynamic Programming Loop: Iterate through the
targetPath
, and for each city, calculate the edit distance by comparing the name of the city with the current target name. Propagate the results to the next state in the DP table.  Reconstruct the Path: Use the
parent
table to reconstruct the path that led to the minimum edit distance.
Here’s the code implementation:


The time complexity of this solution is (O(m \cdot n \cdot d)), where (m) is the length of targetPath
, (n) is the number of cities, and (d) is the maximum degree of a node in the graph. The space complexity is (O(m \cdot n)) for the DP table and parent table.
Identifying Problem Isomorphism
“The Most Similar Path in a Graph” shares some similarities with “Word Ladder II”. Both problems involve finding paths in a graph with certain constraints.
In “The Most Similar Path in a Graph”, you have to find the path in a graph which is most similar to a given target path. The similarity here is typically defined in terms of some form of distance measure, such as the Hamming distance, between the actual path and the target path.
“Word Ladder II” involves transforming one word into another by changing a single character at a time, with each intermediate word being a valid word in a given list. This can be visualized as a graph problem where each word is a node, and there’s an edge between two nodes if one word can be transformed into the other by changing a single character. The task is then to find the shortest transformation sequence, which can be seen as finding the shortest path in the graph.
This is an approximate mapping between these two problems. Their underlying principles involving graph traversal and path finding make them roughly similar. “The Most Similar Path in a Graph” is more complex due to the additional complexity of determining the “most similar” path, compared to simply finding the shortest path in “Word Ladder II”.
10 Prerequisite LeetCode Problems
Here are 10 problems to prepare for “1548. The Most Similar Path in a Graph”. These focus on fundamental concepts of Dynamic Programming and Graph Theory:
 787. Cheapest Flights Within K Stops
 743. Network Delay Time
 279. Perfect Squares
 322. Coin Change
 120. Triangle
 207. Course Schedule
 210. Course Schedule II
 329. Longest Increasing Path in a Matrix
 200. Number of Islands
 542. 01 Matrix
The aim of these problems is to strengthen your understanding and implementation skills of Graph algorithms and Dynamic Programming. Understand how to traverse a graph using DepthFirst Search (DFS) or BreadthFirst Search (BFS), how to deal with weights and distances, and how to formulate and solve subproblems using Dynamic Programming.
Problem Boundary
How to establish the boundary of this problem?
Problem Classification
Problem Statement: 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 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 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
To explain a problem in simple, nontechnical language:
 Can you explain [problem] in simple terms or like you would explain to a nontechnical person?
 Imagine you’re explaining [problem] to someone without a background in programming. How would you describe it?
 If you had to explain [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 [problem]?
 Could you provide a metaphor or everyday example to explain the idea of [problem]?
These prompts encourage an explanation that avoids jargon or assumes minimal technical knowledge, making the concept more accessible to a broader audience.
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 did you infer from the problem statement that this problem can be solved using ?
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
Problem Name:
 What is the problem that you are trying to solve?
Method Name:
 What is the name of the method/function that you are using to solve this problem?
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?
By answering these questions for each method in your program, you can ensure that you have a clear understanding of what each part of your code is doing and how it should behave. This will help prevent bugs and make your code easier to read and maintain.
Problem Decomposition
Problem Name:
 What is the complex problem that you are trying to solve?
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?
By going through these steps for each complex problem, you can break it down into manageable parts, making it much easier to devise an effective solution.
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
What are the reasons for making these mistakes in the given code?
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.