# Mapping Computer Science Problems to Real-World Scenarios: A Comprehensive Guide

Here’s a list with a few examples to get started. Please note that the real-world problems and the algorithms aren’t always a one-to-one match. Different real-world problems might use the same algorithm, and the same real-world problem could be solved using different algorithms depending on the specific use-case.

Sequence | Leetcode Number | Problem Name | Real World Problem | Algorithm |
---|---|---|---|---|

1 | 485 | Max Consecutive Ones | Finding longest continuous stretch of a particular event (e.g., days of rain, streak of good sales) | Sliding Window |

2 | 21 | Merge Two Sorted Lists | Merging two sorted lists of values (e.g., student grades, sales records) | Merge Sort |

3 | 144 | Binary Tree Preorder Traversal | Inventory of goods stored in a hierarchical warehouse | Depth First Search |

4 | 94 | Binary Tree Inorder Traversal | Alphabetical listing of employees in a company hierarchy | Depth First Search |

5 | 148 | Sort List | Organizing a list of customer orders by order number | Merge Sort |

6 | 977 | Squares of a Sorted Array | Ranking cities by the square of their population | Sorting Algorithms |

7 | 283 | Move Zeroes | Rearranging a warehouse, placing lesser used items at the back | Two Pointers |

8 | 145 | Binary Tree Postorder Traversal | Checking a hierarchical to-do list from bottom to top | Depth First Search |

9 | 707 | Design Linked List | Managing the sequence of tasks in a project | Linked List Implementation |

10 | 1089 | Duplicate Zeros | Updating a database with zero entries | Two Pointers |

11 | 141 | Linked List Cycle | Checking for loops in a workflow | Two Pointers/Floyd’s Cycle Finding Algorithm |

12 | 102 | Binary Tree Level Order Traversal | Organizing an agenda according to hierarchical priorities | Breadth First Search |

## Mapping Table

Sequence | Leetcode Number | Problem Name | Real World Problem | Algorithm |
---|---|---|---|---|

1 | 485 | Max Consecutive Ones | Finding longest continuous quality control passes | Array Traversal |

2 | 21 | Merge Two Sorted Lists | Merging two sorted patient lists | Merge Sort |

3 | 144 | Binary Tree Preorder Traversal | Prioritizing tasks in a project | Depth-First Search |

4 | 94 | Binary Tree Inorder Traversal | Cataloguing books in a library system | Depth-First Search |

5 | 148 | Sort List | Sorting a list of employees by ID | Merge Sort |

6 | 977 | Squares of a Sorted Array | Sorting cities by squares of population | Sorting |

7 | 283 | Move Zeroes | Rearranging boxes in a warehouse | Two Pointers |

8 | 145 | Binary Tree Postorder Traversal | Deallocating resources in a dependency order | Depth-First Search |

9 | 707 | Design Linked List | Organizing a to-do list | Linked List Design |

10 | 1089 | Duplicate Zeros | Expanding coded messages | Array Manipulation |

11 | 141 | Linked List Cycle | Detecting circular references in a document | Two Pointers |

12 | 102 | Binary Tree Level Order Traversal | Managing multi-level marketing structure | Breadth-First Search |

13 | 104 | Maximum Depth of Binary Tree | Determining highest level of a business hierarchy | Depth-First Search |

14 | 142 | Linked List Cycle II | Detecting repeat tasks in a project plan | Two Pointers |

15 | 88 | Merge Sorted Array | Merging two ordered lists of customers | Two Pointers |

16 | 75 | Sort Colors | Sorting clothes by color | Dutch National Flag Problem |

17 | 101 | Symmetric Tree | Checking balance in a company’s organization structure | Depth-First Search |

18 | 160 | Intersection of Two Linked Lists | Finding common members in two different teams | Two Pointers |

19 | 27 | Remove Element | Removing discontinued products from a catalog | Two Pointers |

20 | 19 | Remove Nth Node From End of List | Removing a particular item from a task list | Two Pointers |

21 | 112 | Path Sum | Calculating costs on a particular route | Depth-First Search |

22 | 250 | Count Univalue Subtrees | Counting departments with the same performance rating | Depth-First Search |

23 | 206 | Reverse Linked List | Reversing a sequence of events | Linked List Manipulation |

24 | 26 | Remove Duplicates from Sorted Array | Removing duplicate records from a sorted list | Two Pointers |

25 | 1346 | Check If N and Its Double Exist | Checking if an employee’s salary is double another’s | Hash Table |

26 | 100 | Same Tree | Checking if two organization charts are identical | Depth-First Search |

27 | 24 | Swap Nodes in Pairs | Reordering tasks in pairs | Linked List Manipulation |

28 | 941 | Valid Mountain Array | Checking if sales figures form a peak pattern | Array Traversal |

29 | 589 | N-ary Tree Preorder Traversal | Prioritizing tasks in a multi-dependent project | Depth-First Search |

30 |

509 | Fibonacci Number | Predicting rabbit population growth | Dynamic Programming | | 31 | 70 | Climbing Stairs | Counting the ways to climb a staircase | Dynamic Programming | | 32 | 590 | N-ary Tree Postorder Traversal | Completing tasks in a multi-dependent project | Depth-First Search | | 33 | 1299 | Replace Elements with Greatest Element on Right Side | Reordering tasks based on priority | Array Traversal | | 34 | 905 | Sort Array By Parity | Organizing tasks based on type | Two Pointers | | 35 | 50 | Pow(x, n) | Computing an interest rate over time | Binary Search | | 36 | 429 | N-ary Tree Level Order Traversal | Managing a multi-level marketing structure | Breadth-First Search | | 37 | 344 | Reverse String | Reversing a sequence of events | Two Pointers | | 38 | 559 | Maximum Depth of N-ary Tree | Determining highest level of a complex organization | Depth-First Search | | 39 | 22 | Generate Parentheses | Generating valid sequence of operations | Depth-First Search | | 40 | 217 | Contains Duplicate | Checking for duplicate records in a list | Hash Table | | 41 | 431 | Encode N-ary Tree to Binary Tree | Reducing complexity of a project plan | Tree Manipulation | | 42 | 912 | Sort an Array | Sorting a list of items | Quick Sort | | 43 | 33 | Search in Rotated Sorted Array | Searching a cyclically ordered catalog | Binary Search | | 44 | 198 | House Robber | Planning a schedule to maximize profit | Dynamic Programming | | 45 | 700 | Search in a Binary Search Tree | Searching an organized record system | Binary Search | | 46 | 81 | Search in Rotated Sorted Array II | Searching a cyclically ordered catalog with duplicates | Binary Search | | 47 | 98 | Validate Binary Search Tree | Validating an ordered system | Depth-First Search | | 48 | 121 | Best Time to Buy and Sell Stock | Maximizing profit by buying and selling stocks | Dynamic Programming | | 49 | 876 | Middle of the Linked List | Finding the middle item in a list | Two Pointers | | 50 | 270 | Closest Binary Search Tree Value | Finding the closest price in a sorted list | Depth-First Search | | 51 | 153 | Find Minimum in Rotated Sorted Array | Finding the smallest number in a cyclically ordered set | Binary Search | | 52 | 252 | Meeting Rooms | Checking if meeting times overlap | Sorting and Sweep Line | | 53 | 704 | Binary Search | Searching a sorted list of items | Binary Search | | 54 | 83 | Remove Duplicates from Sorted List | Removing duplicate records from a sorted list | Two Pointers | | 55 | 203 | Remove Linked List Elements | Removing specific tasks from a project plan | Two Pointers | | 56 | 852 | Peak Index in a Mountain Array | Finding the peak sales period | Binary Search | | 57 | 637 | Average of Levels in Binary Tree | Averaging performance metrics across an organization | Breadth-First Search | | 58 | 234 | Palindrome Linked List | Checking if a sequence of events is the same forwards and backwards | Two Pointers | | 59 | 111 | Minimum Depth of Binary Tree | Determining the shortest chain of command | Breadth-First Search | | 60 | 162 | Find Peak Element | Finding peak sales period | Binary Search | | 61 | 543 | Diameter of

Binary Tree | Finding the longest communication route in an organization | Depth-First Search | | 62 | 844 | Backspace String Compare | Comparing two versions of a document with edits | Two Pointers | | 63 | 34 | Find First and Last Position of Element in Sorted Array | Locating a specific item in a list | Binary Search | | 64 | 1 | Two Sum | Finding two items that sum to a target price | Hash Table | | 65 | 226 | Invert Binary Tree | Reversing a hierarchy | Tree Traversal | | 66 | 572 | Subtree of Another Tree | Checking if a department exists in two different companies | Depth-First Search | | 67 | 54 | Spiral Matrix | Moving in a patterned sequence | Array Traversal | | 68 | 658 | Find K Closest Elements | Finding the nearest stores to a location | Binary Search | | 69 | 702 | Search in a Sorted Array of Unknown Size | Searching in an unbounded list | Binary Search | | 70 | 235 | Lowest Common Ancestor of a Binary Search Tree | Finding common manager for two employees | Depth-First Search | | 71 | 48 | Rotate Image | Rotating a display image | Array Manipulation | | 72 | 349 | Intersection of Two Arrays | Finding common elements in two lists | Hash Table | | 73 | 79 | Word Search | Searching for a word in a grid of letters | Depth-First Search | | 74 | 617 | Merge Two Binary Trees | Merging two sets of records | Depth-First Search | | 75 | 78 | Subsets | Generating all combinations of a set of items | Backtracking | | 76 | 46 | Permutations | Generating all possible orders of tasks | Backtracking | | 77 | 167 | Two Sum II - Input array is sorted | Finding two items that sum to a target in a sorted list | Two Pointers | | 78 | 287 | Find the Duplicate Number | Finding a duplicate record in a list | Two Pointers | | 79 | 77 | Combinations | Generating all combinations of teams from a set of employees | Backtracking | | 80 | 39 | Combination Sum | Finding combinations of items that total a target cost | Backtracking | | 81 | 4 | Median of Two Sorted Arrays | Finding the median of combined records | Binary Search | | 82 | 494 | Target Sum | Finding combinations of items that total a target cost with restrictions | Dynamic Programming | | 83 | 442 | Find All Duplicates in an Array | Finding duplicate records in a list | Array Traversal | | 84 | 1065 | Index Pairs of a String | Finding positions of words in a document | Hash Table | | 85 | 73 | Set Matrix Zeroes | Removing all instances of a product from a matrix of orders | Array Traversal | | 86 | 448 | Find All Numbers Disappeared in an Array | Finding missing items in a list | Array Traversal | | 87 | 238 | Product of Array Except Self | Calculating product totals without self | Array Manipulation | | 88 | 131 | Palindrome Partitioning | Dividing a word into palindrome sections | Dynamic Programming | | 89 | 17 | Letter Combinations of a Phone Number | Generating all word combinations from a phone number | Backtracking | | 90 | 169 | Majority Element | Finding most common item in a list | Boyer-Moore Voting Algorithm | | 91 | 322 | Coin Change | Finding the fewest coins that make a certain value | Dynamic Programming | | 92 | 320

| Generalized Abbreviation | Creating all possible abbreviations for a word | Backtracking | | 93 | 20 | Valid Parentheses | Checking if brackets in a document are balanced | Stack | | 94 | 51 | N-Queens | Organizing tasks so none conflict | Backtracking | | 95 | 236 | Lowest Common Ancestor of a Binary Tree | Finding common manager for two employees in a company | Depth-First Search | | 96 | 283 | Move Zeroes | Rearranging boxes in a warehouse | Two Pointers | | 97 | 89 | Gray Code | Generating a gray code sequence | Bit Manipulation | | 98 | 200 | Number of Islands | Counting separate groups in an organization | Depth-First Search | | 99 | 15 | 3Sum | Finding three items that sum to a target price | Two Pointers | | 100 | 42 | Trapping Rain Water | Calculating the maximum amount of water trapped | Two Pointers |

Note: These are broad examples and the real-world applications of these algorithms may vary based on specific use cases. The same real-world problem could be solved using different algorithms or data structures, and the same algorithm could be used to solve different real-world problems.

Here is the same table for more problems:

Problem Name | Real World Problem | Algorithm |
---|---|---|

Palindromic Substrings | Checking for reversible words in a document | Dynamic Programming |

Number of Longest Increasing Subsequence | Finding longest sequence of progress in life events | Dynamic Programming |

Partition Equal Subset Sum | Distributing tasks equally among workers | Dynamic Programming |

Number of Islands | Identifying separated land masses on a map | Depth-First Search |

Pacific Atlantic Water Flow | Determining water flow in geographical terrains | Depth-First Search |

Clone Graph | Copying social network connections | Breadth-First Search/Depth-First Search |

Reorder List | Arranging documents in a particular order | Two Pointers |

Sort List | Arranging items in an inventory | Merge Sort |

Remove Nth Node From End of List | Removing a particular item from a list | Two Pointers |

Add Two Numbers | Performing large number arithmetic | Linked List |

Best Time to Buy and Sell Stock with Cooldown | Optimizing stock trading with cooldowns | Dynamic Programming |

Odd Even Linked List | Organizing a list into odd and even indices | Two Pointers |

Swap Nodes in Pairs | Pairing and swapping items in a list | Linked List |

Rotate List | Rotating items in a list | Two Pointers |

Number of Connected Components in an Undirected Graph | Counting groups in a social network | Depth-First Search/Breadth-First Search |

Graph Valid Tree | Checking if a network can be organized as a tree | Depth-First Search |

Task Scheduler | Scheduling tasks with cooldowns | Heap/Priority Queue |

Non-overlapping Intervals | Scheduling meetings in different rooms | Greedy Algorithm |

Interval List Intersections | Finding overlaps in schedules | Two Pointers |

Merge Intervals | Merging overlapping time intervals | Sorting |

Find K Pairs with Smallest Sums | Finding most compatible pairs in two groups | Heap |

Kth Smallest Element in a Sorted Matrix | Finding a rank in a competition | Binary Search |

Find K Closest Elements | Finding closest locations to a point | Binary Search |

Search a 2D Matrix II | Searching a database | Binary Search |

Search a 2D Matrix | Searching a database | Binary Search |

Search in Rotated Sorted Array II | Searching for an item in a shifted database | Binary Search |

Search in Rotated Sorted Array | Searching for an item in a shifted database | Binary Search |

Find Peak Element | Finding a local maximum in a graph | Binary Search |

Find Minimum in Rotated Sorted Array | Finding a local minimum in a shifted graph | Binary Search |

Minimum Number of Arrows to Burst Balloons | Strategizing in a balloon shooting game | Greedy Algorithm |

Minimum Height Trees | Finding the minimum height trees in a forest | Breadth-First Search |

Course Schedule II | Scheduling university courses | Depth-First Search |

Course Schedule | Checking if a university course schedule is possible | Depth-First Search |

Reorganize String | Arranging characters in a way to avoid repetition | Heap |

Kth Largest Element in an Array | Finding a rank in a competition | Heap |

Sort Characters By Frequency | Counting character frequency in a document | Heap |

Top K Frequent Elements | Identifying the most frequent items in a database | Heap |

K Closest Points to Origin | Finding the nearest locations to a point | Heap |

Kth Smallest Element in a BST | Finding a rank in a competition | Binary Search Tree |

Longest Repeating Character Replacement | Modifying a document to create long repeated character strings | Two Pointers |

Permutation in String | Checking if a document contains any anagram of a word | Two Pointers |

Fruit Into Baskets | Optimizing collection of different types of items | Two Pointers |

Minimum Size Subarray Sum | Minimizing a window to meet a certain criteria | Two Pointers |

3Sum | Finding triplets in a set that add up to a certain number | Two Pointers |

Implement Trie (Prefix Tree) | Autocompleting a search query | Trie |

3Sum Closest | Finding triplets closest to a target sum | Two Pointers |

Validate Binary Search Tree | Checking if a book index follows a binary search tree property | Depth-First Search |

Construct Binary Tree from Preorder and Inorder Traversal | Constructing a family tree given certain properties | Depth-First Search |

Maximum Width of Binary Tree | Finding the maximum width of a hierarchy | Depth-First Search |

Maximum Binary Tree | Constructing a hierarchy with maximum property | Depth-First Search |

Path Sum III | Finding all the paths in a financial tree that sum to a certain amount | Depth-First Search |

Path Sum II | Finding all the paths in a project tree that sum to a certain amount | Depth-First Search |

All Nodes Distance K in Binary Tree | Finding all nodes at a certain distance in a network | Breadth-First Search |

Binary Tree Right Side View | Viewing a hierarchy from a certain angle | Depth-First Search |

Populating Next Right Pointers in Each Node II | Linking elements in a hierarchy | Breadth-First Search |

Populating Next Right Pointers in Each Node | Linking elements in a hierarchy | Breadth-First Search |

Binary Tree Zigzag Level Order Traversal | Traversing a hierarchy in a zigzag pattern | Breadth-First Search |

Longest Substring Without Repeating Characters | Finding the longest unique section in a document | Sliding Window |

Sliding Window Maximum | Finding the maximum in each window of a list | Deque |

Count of Range Sum | Counting the number of sums in a range | Merge Sort |

Graph Valid Tree | Checking if a network can be organized as a tree | Depth-First Search |

Meeting Rooms II | Scheduling meeting rooms | Heap |

Insert Interval | Inserting an interval in a schedule | Sorting |

Container With Most Water | Maximizing water storage between points | Two Pointers |

Trapping Rain Water | Calculating rainwater trapped between buildings | Two Pointers |

Sequence Reconstruction | Checking if a sequence can be reconstructed from subsequences | Topological Sort |

Alien Dictionary | Constructing a dictionary from alien words | Topological Sort |

## Real World Applications

Here’s the table for the problems along with a column for real-world applications:

Problem Name | Real World Problem | Algorithm | Real World Application/Product |
---|---|---|---|

N-Queens | Positioning multiple servers to avoid interference | Backtracking | GPS positioning systems |

Smallest Range Covering Elements from K Lists | Finding a minimal range in different measurements | Heap | Climate change analysis |

Merge k Sorted Lists | Merging multiple sorted datasets | Heap | Database management systems |

Reverse Nodes in k-Group | Reversing sections of a list | Linked List | Data manipulation in Excel |

Sudoku Solver | Solving a Sudoku game | Backtracking | Sudoku apps |

Longest Consecutive Sequence | Finding the longest streak in data | Hashing | Activity trackers like Fitbit |

First Missing Positive | Finding missing information in data | Array manipulation | Database management |

Maximum XOR of Two Numbers in an Array | Finding the maximum XOR operation result | Trie | Data encryption |

Sort Colors | Sorting data by categories | Two Pointers | Inventory management systems |

Subarray Product Less Than K | Finding product sections within a limit | Two Pointers | Inventory forecasting |

Substring with Concatenation of All Words | Finding all words in a document | Sliding Window | Search engines like Google |

Minimum Window Substring | Finding the smallest relevant section in a document | Sliding Window | Text Editors |

Count Unique Characters of All Substrings of a Given String | Counting unique substrings | Sliding Window | Data compression software |

Minimum Number of K Consecutive Bit Flips | Manipulating bit data | Sliding Window | Network protocol design |

Employee Free Time | Finding free time in employee schedules | Heap | HR software like Workday |

Smallest Range Covering Elements from K Lists | Finding a minimal range in different measurements | Heap | Climate change analysis |

Median of Two Sorted Arrays | Finding the median from multiple datasets | Binary Search | Statistics software |

Sort Items by Groups Respecting Dependencies | Sorting tasks considering dependencies | Topological Sort | Project management tools like Asana |

Word Squares | Forming words in a grid | Trie, Backtracking | Crossword puzzle generators |

Design Search Autocomplete System | Autocompleting a search query | Trie, Heap | Google Search |

Palindrome Pairs | Finding palindrome pairs | Trie, Hashing | Data analysis software |

Prefix and Suffix Search | Searching for words with certain prefixes and suffixes | Trie | Google Search |

Concatenated Words | Finding concatenated words | Dynamic Programming | Natural language processing tools |

Sliding Window Median | Finding the median in a sliding window | Sliding Window, Heap | Real-time data analysis tools |

Find Median from Data Stream | Finding the median in a data stream | Heap | Real-time data analysis tools |

Word Search II | Searching for multiple words in a grid | Trie, Depth-First Search | Word search game apps |

Serialize and Deserialize Binary Tree | Storing and retrieving tree structures | Depth-First Search | Database systems |

Binary Tree Maximum Path Sum | Finding the maximum path sum in a tree | Depth-First Search | Network routing algorithms |

Maximum Frequency Stack | Designing a stack with maximum frequency retrieval | Stack, Heap | Cache design |

Course Schedule III | Scheduling tasks with deadlines | Heap | Project management tools like Trello |

Rearrange String k Distance Apart | Arranging tasks with minimum gap | Heap, Queue | CPU task scheduling |

Substring with Concatenation of All Words | Finding all words in a document | Sliding Window | Search engines like Google |

Sliding Window Maximum | Finding the maximum |

in each window of a list | Deque | Real-time data analysis tools | | Count of Range Sum | Counting the number of sums in a range | Merge Sort | Financial analysis software |

I can provide potential real-world applications or product scenarios where these problems might be relevant:

First Bad Version (278)

- Problem Category: Binary Search
- Real World Problem: Identifying the point of failure in a sequence of system versions.
- Algorithm: Binary Search
- Application: Software versioning systems in companies like Microsoft, Apple, etc. where it’s crucial to identify the exact version where a bug was introduced.

Pascal’s Triangle II (119)

- Problem Category: Dynamic Programming
- Real World Problem: Calculating the specific row of mathematical structure Pascal’s Triangle.
- Algorithm: Dynamic Programming
- Application: In mathematical software or tools (like Mathematica, MATLAB) where computation of combinatorial mathematics is needed.

Valid Perfect Square (367)

- Problem Category: Binary Search
- Real World Problem: Checking if a given number is a perfect square.
- Algorithm: Binary Search
- Application: In geometry-based software tools or mathematical modeling software where calculations involving squares and roots are frequently required.

Find Smallest Letter Greater Than Target (744)

- Problem Category: Binary Search
- Real World Problem: Searching for the next larger element in a cyclically sorted list.
- Algorithm: Binary Search
- Application: In text-editing or word-processing software (like Microsoft Word, Google Docs), such a feature might be used for providing suggestions or autocompletions.

Find K-th Smallest Pair Distance (719)

- Problem Category: Binary Search, Sliding Window
- Real World Problem: Finding the k-th smallest distance among all possible pair distances in a list.
- Algorithm: Binary Search and Sliding Window
- Application: In geographic information systems (GIS) or navigation applications (like Google Maps), this problem could relate to finding the k-th shortest distance between pairs of locations.

Split Array Largest Sum (410)

- Problem Category: Binary Search, Dynamic Programming
- Real World Problem: Dividing an array into sections to minimize the largest sum of any section.
- Algorithm: Binary Search and Dynamic Programming
- Application: This type of problem might come up in resource allocation in cloud services (like Amazon AWS, Google Cloud) where workloads need to be evenly distributed across different servers to prevent overloading any particular one.