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12 changes: 6 additions & 6 deletions Arrays/README.md
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Expand Up @@ -4,10 +4,10 @@ This directory contains Python implementations of common array-based algorithms

## Contents

- [Anagram Check (Sorted Solution)](Anagram_Check_Sorted_Sol.py): Checks if two strings are anagrams by comparing their sorted versions.
- [Anagram Check (Manual Solution)](Anagram_Check_manual_Sol.py): Checks if two strings are anagrams using a hash table (dictionary) to count character frequencies.
- [Array Find Missing Element (XOR Solution)](ArrayFindTheMissingElement_XOR_sol.py): Efficiently finds a missing element in a shuffled array using bitwise XOR.
- [Array Find Missing Element (Brute Force Solution)](ArrayFindTheMissingElement_brute_force_sol.py): Finds a missing element by sorting both arrays and comparing them.
- [Array Find Missing Element (Hash Table Solution)](ArrayFindTheMissingElement_hash_table_sol.py): Finds a missing element using a hash table (dictionary) to track element counts.
- [Array Find Missing Element (Sum/Subtract Solution)](ArrayFindTheMissingElement_takingSumandSubtract_sol.py): Finds a missing element by calculating the difference between the sums of the two arrays.
- [Anagram Check (Sorted Solution)](AnagramCheckSortedSol.py): Checks if two strings are anagrams by comparing their sorted versions. $O(n \log n)$
- [Anagram Check (Manual Solution)](AnagramCheckManualSol.py): Checks if two strings are anagrams using a hash table (dictionary) to count character frequencies. $O(n)$
- [Array Find Missing Element (XOR Solution)](ArrayFindTheMissingElementXORSol.py): Efficiently finds a missing element in a shuffled array using bitwise XOR. $O(n)$
- [Array Find Missing Element (Brute Force Solution)](ArrayFindTheMissingElementBruteForceSol.py): Finds a missing element by sorting both arrays and comparing them. $O(n \log n)$
- [Array Find Missing Element (Hash Table Solution)](ArrayFindTheMissingElementHashTableSol.py): Finds a missing element using a hash table (dictionary) to track element counts. $O(n)$
- [Array Find Missing Element (Sum/Subtract Solution)](ArrayFindTheMissingElementSumSol.py): Finds a missing element by calculating the difference between the sums of the two arrays. $O(n)$
- [Array Pair Sum Solution](ArrayPairSumSol.py): Finds all unique pairs in an array that sum up to a specific value $k$ using a set for $O(n)$ complexity.
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2 changes: 1 addition & 1 deletion deque/README.md → Deque/README.md
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Expand Up @@ -4,4 +4,4 @@ This directory contains Python implementations of the Deque (Double-Ended Queue)

## Contents

- [Deque Implementation](DequeImple.py): Basic implementation of a Deque using a Python list. Includes operations like `addFront`, `addRear`, `removeFront`, `removeRear`, `isEmpty`, and `size`.
- [Deque Implementation](DequeImple.py): Basic implementation of a Deque using a Python list. Includes operations like `addFront` and `removeFront` ($O(1)$), and `addRear` and `removeRear` ($O(n)$).
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12 changes: 6 additions & 6 deletions GraphAlgorithms/README.md
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Expand Up @@ -4,9 +4,9 @@ This directory contains Python implementations of common graph-based algorithms

## Contents

- [Adjacency List Implementation](AdjacencyListGraphImple.py): Implements the Graph Abstract Data Type (ADT) using an adjacency list (dictionaries in Python). Includes `Vertex` and `Graph` classes.
- [Breadth First Search (BFS)](BFS.py): Implements BFS to solve the Word Ladder problem, finding the shortest transformation path between words.
- [General Depth First Search (DFS)](DFSGeneral.py): Provides a general implementation of DFS, including discovery and finish times for vertices.
- [DFS - Knight's Tour Problem](DFSImpleTheKnightsTourProblem.py): Another implementation of DFS specifically tailored to the Knight's Tour puzzle.
- [The Knight's Tour Problem](TheKnightsTourProblem.py): Focuses on generating the knight's move graph and solving the tour using DFS and backtracking.
- [Word Ladder Problem](WordLadderProblem.py): Specifically focuses on building the word ladder graph where edges connect words that differ by only one letter.
- [Adjacency List Implementation](AdjacencyListGraphImple.py): Implements the Graph Abstract Data Type (ADT) using an adjacency list (dictionaries in Python). Includes `Vertex` and `Graph` classes. $O(V+E)$
- [Breadth First Search (BFS)](BFS.py): Implements BFS to solve the Word Ladder problem, finding the shortest transformation path between words. $O(V+E)$
- [General Depth First Search (DFS)](DFSGeneral.py): Provides a general implementation of DFS, including discovery and finish times for vertices. $O(V+E)$
- [DFS - Knight's Tour Problem](DFSImpleTheKnightsTourProblem.py): Another implementation of DFS specifically tailored to the Knight's Tour puzzle. $O(2^N)$
- [The Knight's Tour Problem](TheKnightsTourProblem.py): Focuses on generating the knight's move graph and solving the tour using DFS and backtracking. $O(2^N)$
- [Word Ladder Problem](WordLadderProblem.py): Specifically focuses on building the word ladder graph where edges connect words that differ by only one letter. $O(n \cdot L^2)$
8 changes: 4 additions & 4 deletions LinkedLists/README.md
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Expand Up @@ -4,8 +4,8 @@ This directory contains Python implementations of various types of linked lists

## Contents

- [Singly Linked List Implementation](SingleLinkedListImple.py): Basic implementation of a singly linked list node and basic linkage.
- [Doubly Linked List Implementation](DoublyLinkedListImple.py): Basic implementation of a doubly linked list node with `prev` and `next` pointers.
- [Singly Linked List Cycle Check](SinglyLinkedListCycleCheckImple.py): Implements Floyd's Cycle-Finding Algorithm (two pointers) to detect cycles in a linked list.
- [Singly Linked List Implementation](SingleLinkedListImple.py): Basic implementation of a singly linked list node and basic linkage. $O(1)$ node creation.
- [Doubly Linked List Implementation](DoublyLinkedListImple.py): Basic implementation of a doubly linked list node with `prev` and `next` pointers. $O(1)$ node creation.
- [Singly Linked List Cycle Check](SinglyLinkedListCycleCheckImple.py): Implements Floyd's Cycle-Finding Algorithm (two pointers) to detect cycles in a linked list. $O(n)$
- [Linked List Reversal](LinkedListReversal.py): Reverses a singly linked list in-place in $O(n)$ time.
- [Nth to Last Node](LinkedListNthToLastNode.py): Finds the $n$-th to last node in a singly linked list using two pointers.
- [Nth to Last Node](LinkedListNthToLastNode.py): Finds the $n$-th to last node in a singly linked list using two pointers. $O(n)$
4 changes: 2 additions & 2 deletions Queues/README.md
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Expand Up @@ -4,5 +4,5 @@ This directory contains Python implementations of the Queue data structure.

## Contents

- [Queue Implementation](QueueImple.py): Basic implementation of a FIFO (First-In-First-Out) queue using a Python list. Includes `enqueue`, `dequeue`, `isEmpty`, and `size` methods.
- [Queue with Two Stacks](QueueWith2StacksImple.py): Implements a queue using two stacks (represented by Python lists) to achieve FIFO behavior.
- [Queue Implementation](QueueImple.py): Basic implementation of a FIFO (First-In-First-Out) queue using a Python list. Includes `enqueue` ($O(n)$) and `dequeue` ($O(1)$) methods.
- [Queue with Two Stacks](QueueWith2StacksImple.py): Implements a queue using two stacks (represented by Python lists) to achieve FIFO behavior. $O(1)$ amortized for both operations.
40 changes: 20 additions & 20 deletions README.md
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Expand Up @@ -38,17 +38,17 @@ See [CONTRIBUTING.md](CONTRIBUTING.md) for more details.
- [Getting Started](#getting-started)
- [Project Structure](#project-structure)
- [Data Structures](#data-structures)
- [Arrays](#arrays)
- [Linked Lists](#linked-lists)
- [Stacks](#stacks)
- [Queues](#queues)
- [Deque](#deque)
- [Trees](#trees)
- [Algorithms](#algorithms)
- [Sorting](#sorting)
- [Recursion & Dynamic Programming](#recursion--dynamic-programming)
- [Graph Algorithms](#graph-algorithms)
- [Error Handling & Debugging](#error-handling--debugging)
- [Arrays](#arrays-)
- [Linked Lists](#linked-lists-)
- [Stacks](#stacks-)
- [Queues](#queues-)
- [Deque](#deque-)
- [Trees](#trees-)
- [Algorithms](#algorithms-)
- [Sorting](#sorting-)
- [Recursion & Dynamic Programming](#recursion--dynamic-programming-)
- [Graph Algorithms](#graph-algorithms-)
- [Error Handling & Debugging](#error-handling--debugging-)
- [Usage](#usage)
- [Quick Reference](#quick-reference)
- [License](#license)
Expand All @@ -67,7 +67,7 @@ Most scripts in this repository are standalone and can be executed directly:

```bash
# Run any Python script
python3 Arrays/Anagram_Check_Sorted_Sol.py
python3 Arrays/AnagramCheckSortedSol.py

# Or run from the repo root
python3 Sorting/BubbleSortImple.py
Expand All @@ -80,15 +80,15 @@ python3 Sorting/BubbleSortImple.py
```
.
├── Arrays/ # 🔤 Array-based problems and algorithms
├── Error-debug/ # ⚠️ Error handling and debugging examples
├── Deque/ # 🔄 Double-ended queue
├── ErrorHandling/ # ⚠️ Error handling and debugging examples
├── GraphAlgorithms/ # 🗺️ Graph traversal (BFS, DFS) and pathfinding
├── LinkedLists/ # 🔗 Singly and Doubly Linked Lists
├── Queues/ # 📦 Queue implementations (FIFO)
├── Recursion/ # 🔀 Recursive problems and Dynamic Programming
├── Sorting/ # 📊 Common sorting algorithms
├── Stacks/ # 📚 Stack implementations and applications
├── Trees/ # 🌳 Binary Trees, BSTs, Heaps, and Traversals
├── deque/ # 🔄 Double-ended queue
├── CONTRIBUTING.md # 🤝 Contribution guidelines
├── LICENSE # 📄 MIT License
└── README.md # 📖 This file
Expand All @@ -100,9 +100,9 @@ python3 Sorting/BubbleSortImple.py

### Arrays 🔤
Common array-based algorithms and manipulations.
- [Anagram Check](Arrays/): [Sorted](Arrays/Anagram_Check_Sorted_Sol.py) & [Manual](Arrays/Anagram_Check_manual_Sol.py) solutions
- [Anagram Check](Arrays/): [Sorted](Arrays/AnagramCheckSortedSol.py) & [Manual](Arrays/AnagramCheckManualSol.py) solutions
- [Array Pair Sum](Arrays/ArrayPairSumSol.py): Find pairs that sum to $k$
- [Find Missing Element](Arrays/): [XOR](Arrays/ArrayFindTheMissingElement_XOR_sol.py), [Brute Force](Arrays/ArrayFindTheMissingElement_brute_force_sol.py), [Hash Table](Arrays/ArrayFindTheMissingElement_hash_table_sol.py), & [Sum](Arrays/ArrayFindTheMissingElement_takingSumandSubtract_sol.py) approaches
- [Find Missing Element](Arrays/): [XOR](Arrays/ArrayFindTheMissingElementXORSol.py), [Brute Force](Arrays/ArrayFindTheMissingElementBruteForceSol.py), [Hash Table](Arrays/ArrayFindTheMissingElementHashTableSol.py), & [Sum](Arrays/ArrayFindTheMissingElementSumSol.py) approaches

### Linked Lists 🔗
Implementations and problems involving linked structures.
Expand All @@ -123,7 +123,7 @@ FIFO (First-In-First-Out) data structures.

### Deque 🔄
Double-ended queue operations.
- [Deque Implementation](deque/DequeImple.py): Operations at both ends
- [Deque Implementation](Deque/DequeImple.py): Operations at both ends

### Trees 🌳
Hierarchical data structures.
Expand All @@ -133,7 +133,7 @@ Hierarchical data structures.
- [Binary Heap](Trees/BinaryHeapImple.py): Min-heap implementation
- [Tree Traversals](Trees/TreeLevelOrderPrintImple.py): Level order (BFS) printing
- [Trim BST](Trees/TrimBinarySearchTreeImple.py): Keep nodes within a range
- [Tree Representations](Trees/): [Nodes & References](Trees/TreeRepresentationWithNodesReferences.py) & [List of Lists](Trees/buildTreeTest.py)
- [Tree Representations](Trees/): [Nodes & References](Trees/TreeRepresentationWithNodesReferences.py) & [List of Lists](Trees/BuildTreeTest.py)

---

Expand All @@ -144,7 +144,7 @@ Algorithms for arranging elements in order.
- [Bubble Sort](Sorting/BubbleSortImple.py) - $O(n^2)$
- [Selection Sort](Sorting/SelectionSortImple.py) - $O(n^2)$
- [Insertion Sort](Sorting/InsertionSortImple.py) - $O(n^2)$
- [Shell Sort](Sorting/ShellSortImple.py) - $O(n \log n)$
- [Shell Sort](Sorting/ShellSortImple.py) - $O(n^2)$
- [Merge Sort](Sorting/MergeSortImple.py) - $O(n \log n)$
- [Quick Sort](Sorting/QuickSortImple.py) - $O(n \log n)$ average

Expand All @@ -168,7 +168,7 @@ Algorithms for graph traversal and pathfinding.

## ⚠️ Error Handling & Debugging

- [Error and Exceptions](Error-debug/ErrorExceptions.py): Demonstrates `try`, `except`, `else`, and `finally` blocks for robust error handling.
- [Error and Exceptions](ErrorHandling/ErrorExceptions.py): Demonstrates `try`, `except`, `else`, and `finally` blocks for robust error handling.

---

Expand Down
20 changes: 10 additions & 10 deletions Recursion/README.md
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Expand Up @@ -5,17 +5,17 @@ This directory contains Python implementations of problems solved using recursio
## Contents

### Fibonacci Sequence
- [Fibonacci (Iterative)](FibonacciSeqIterative.py): Iterative implementation of the Fibonacci sequence.
- [Fibonacci (Recursive)](FibonacciSeqRecursion.py): Simple recursive implementation of the Fibonacci sequence.
- [Fibonacci (Dynamic Programming)](FibonacciSeqDynamic.py): Optimized Fibonacci sequence using memoization.
- [Fibonacci (Iterative)](FibonacciSeqIterative.py): Iterative implementation of the Fibonacci sequence. $O(n)$
- [Fibonacci (Recursive)](FibonacciSeqRecursion.py): Simple recursive implementation of the Fibonacci sequence. $O(2^n)$
- [Fibonacci (Dynamic Programming)](FibonacciSeqDynamic.py): Optimized Fibonacci sequence using memoization. $O(n)$

### Coin Change Problem
- [Coin Change (Recursive)](CoinChangeProblemRecursion.py): Basic recursive solution to find the minimum number of coins for change.
- [Coin Change (Dynamic Programming)](CoinChangeProblemDynamic.py): Optimized solution to the coin change problem using dynamic programming.
- [Coin Change (Recursive)](CoinChangeProblemRecursion.py): Basic recursive solution to find the minimum number of coins for change. $O(2^n)$
- [Coin Change (Dynamic Programming)](CoinChangeProblemDynamic.py): Optimized solution to the coin change problem using dynamic programming. $O(n \cdot m)$

### Other Recursive Problems
- [Cumulative Sum](RecursionCumulativeSum.py): Computes the cumulative sum from 0 to $n$ recursively.
- [Reverse a String](RecursionReverseStr.py): Reverses a string using recursive calls.
- [String Permutations](RecursionStrPermutation.py): Generates all possible permutations of a given string.
- [Sum of Digits](RecursionSumOfDigits.py): Calculates the sum of all individual digits in an integer recursively.
- [Word Split](RecursionWordSplit.py): Determines if a string can be split into words from a given list.
- [Cumulative Sum](RecursionCumulativeSum.py): Computes the cumulative sum from 0 to $n$ recursively. $O(n)$
- [Reverse a String](RecursionReverseStr.py): Reverses a string using recursive calls. $O(n)$
- [String Permutations](RecursionStrPermutation.py): Generates all possible permutations of a given string. $O(n!)$
- [Sum of Digits](RecursionSumOfDigits.py): Calculates the sum of all individual digits in an integer recursively. $O(\log_{10} n)$
- [Word Split](RecursionWordSplit.py): Determines if a string can be split into words from a given list. $O(2^n)$
8 changes: 4 additions & 4 deletions Sorting/README.md
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Expand Up @@ -5,8 +5,8 @@ This directory contains Python implementations of various sorting algorithms wit
## Contents

- [Bubble Sort](BubbleSortImple.py): Implementation of Bubble Sort with $O(n^2)$ complexity.
- [Selection Sort](SelectionSortImple.py): Implementation of Selection Sort, improving on Bubble Sort by making only one exchange per pass.
- [Insertion Sort](InsertionSortImple.py): Implementation of Insertion Sort, maintaining a sorted sublist.
- [Shell Sort](ShellSortImple.py): Implementation of Shell Sort (diminishing increment sort), improving on Insertion Sort.
- [Selection Sort](SelectionSortImple.py): Implementation of Selection Sort, improving on Bubble Sort by making only one exchange per pass. $O(n^2)$
- [Insertion Sort](InsertionSortImple.py): Implementation of Insertion Sort, maintaining a sorted sublist. $O(n^2)$
- [Shell Sort](ShellSortImple.py): Implementation of Shell Sort (diminishing increment sort), improving on Insertion Sort. $O(n^2)$ worst case.
- [Merge Sort](MergeSortImple.py): A recursive "divide and conquer" algorithm with $O(n \log n)$ complexity.
- [Quick Sort](QuickSortImple.py): Implementation of Quick Sort (partition exchange sort), using divide and conquer in-place.
- [Quick Sort](QuickSortImple.py): Implementation of Quick Sort (partition exchange sort), using divide and conquer in-place. $O(n \log n)$ average.
4 changes: 2 additions & 2 deletions Stacks/README.md
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Expand Up @@ -4,5 +4,5 @@ This directory contains Python implementations of the Stack data structure and i

## Contents

- [Stack Implementation](StackImple.py): Basic implementation of a LIFO (Last-In-First-Out) stack using a Python list. Includes `push`, `pop`, `peek`, `isEmpty`, and `size` methods.
- [Balanced Parentheses Check](BalanceParenthlessCheckImple.py): Uses a stack to check if a string of opening and closing parentheses (round, square, and curly) is balanced.
- [Stack Implementation](StackImple.py): Basic implementation of a LIFO (Last-In-First-Out) stack using a Python list. Includes `push` and `pop` ($O(1)$) methods.
- [Balanced Parentheses Check](BalanceParenthlessCheckImple.py): Uses a stack to check if a string of opening and closing parentheses (round, square, and curly) is balanced. $O(n)$
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