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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 ($O(n)$ time, $O(1)$ space).
- [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` ($O(1)$), `addRear` ($O(n)$), `removeFront` ($O(1)$), `removeRear` ($O(n)$), `isEmpty` ($O(1)$), and `size` ($O(1)$).
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2 changes: 1 addition & 1 deletion Error-debug/README.md → ErrorHandling/README.md
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@@ -1,4 +1,4 @@
# Error and Debugging
# Error Handling and Debugging

This directory contains examples of error handling and debugging techniques in Python.

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6 changes: 3 additions & 3 deletions GraphAlgorithms/README.md
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Expand Up @@ -5,8 +5,8 @@ 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.
- [Breadth First Search (BFS)](BFS.py): Implements BFS to solve the Word Ladder problem ($O(V+E)$).
- [General Depth First Search (DFS)](DFSGeneral.py): Provides a general implementation of DFS ($O(V+E)$).
- [DFS - Knight's Tour Problem](DFSImpleTheKnightsTourProblem.py): Another implementation of DFS specifically tailored to the Knight's Tour puzzle ($O(k^N)$).
- [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.
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 ($O(1)$ for basic insertion/deletion).
- [Doubly Linked List Implementation](DoublyLinkedListImple.py): Basic implementation of a doubly linked list node with `prev` and `next` pointers ($O(1)$).
- [Singly Linked List Cycle Check](SinglyLinkedListCycleCheckImple.py): Implements Floyd's Cycle-Finding Algorithm (two pointers) to detect cycles ($O(n)$).
- [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` ($O(n)$), `dequeue` ($O(1)$), `isEmpty` ($O(1)$), and `size` ($O(1)$) methods.
- [Queue with Two Stacks](QueueWith2StacksImple.py): Implements a queue using two stacks to achieve FIFO behavior ($O(1)$ amortized).
50 changes: 25 additions & 25 deletions README.md
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Expand Up @@ -35,23 +35,23 @@ See [CONTRIBUTING.md](CONTRIBUTING.md) for more details.

## 📖 Table of Contents

- [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)
- [Usage](#usage)
- [Quick Reference](#quick-reference)
- [License](#license)
- [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)
- [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 Down Expand Up @@ -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.

---

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16 changes: 8 additions & 8 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 (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.
- [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.
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` ($O(1)$), `pop` ($O(1)$), `peek` ($O(1)$), `isEmpty` ($O(1)$), and `size` ($O(1)$) methods.
- [Balanced Parentheses Check](BalanceParenthlessCheckImple.py): Uses a stack to check if a string of opening and closing parentheses is balanced ($O(n)$).
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18 changes: 9 additions & 9 deletions Trees/README.md
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Expand Up @@ -5,19 +5,19 @@ This directory contains Python implementations of various tree-based data struct
## Contents

### Binary Search Trees (BST)
- [Binary Search Tree Implementation](BinarySearchTreesImple.py): A comprehensive implementation of a BST with `TreeNode` and `BinarySearchTree` classes, including insertion, deletion, and search.
- [Validate BST (Solution 1)](BinarySearchTreeCheckImpleSol1.py): Validates a BST by performing an in-order traversal and checking if the resulting values are sorted.
- [Validate BST (Solution 2)](BinarySearchTreeCheckImpleSol2.py): Validates a BST by keeping track of the minimum and maximum allowable values for each node.
- [Trim a BST](TrimBinarySearchTreeImple.py): Trims a BST so that all node values fall within a specified range $[min, max]$.
- [Binary Search Tree Implementation](BinarySearchTreesImple.py): A comprehensive implementation of a BST ($O(\log n)$ average, $O(n)$ worst).
- [Validate BST (Solution 1)](BinarySearchTreeCheckImpleSol1.py): Validates a BST by performing an in-order traversal ($O(n)$).
- [Validate BST (Solution 2)](BinarySearchTreeCheckImpleSol2.py): Validates a BST by keeping track of the minimum and maximum allowable values ($O(n)$).
- [Trim a BST](TrimBinarySearchTreeImple.py): Trims a BST so that all node values fall within a specified range ($O(n)$).

### Search Algorithms
- [Binary Search (Iterative)](BinarySearchImple.py): Iterative implementation of the binary search algorithm on a sorted list.
- [Binary Search (Recursive)](BinarySearchRecursiveImple.py): Recursive implementation of the binary search algorithm.
- [Binary Search (Iterative)](BinarySearchImple.py): Iterative implementation of the binary search algorithm ($O(\log n)$).
- [Binary Search (Recursive)](BinarySearchRecursiveImple.py): Recursive implementation of the binary search algorithm ($O(\log n)$).

### Heaps
- [Binary Heap Implementation](BinaryHeapImple.py): Implements a min-heap using a recursive approach, including `insert`, `delMin`, and `buildHeap`.
- [Binary Heap Implementation](BinaryHeapImple.py): Implements a min-heap, including `insert` ($O(\log n)$) and `delMin` ($O(\log n)$).

### Tree Representations & Traversals
- [Nodes and References Representation](TreeRepresentationWithNodesReferences.py): A simple implementation of a binary tree using a class-based nodes and references approach.
- [List of Lists Representation](buildTreeTest.py): Demonstrates building and manipulating a tree using a "list of lists" approach.
- [Tree Level Order Print](TreeLevelOrderPrintImple.py): Prints a binary tree in level order (breadth-first) using a queue, with each level on a new line.
- [List of Lists Representation](BuildTreeTest.py): Demonstrates building and manipulating a tree using a "list of lists" approach.
- [Tree Level Order Print](TreeLevelOrderPrintImple.py): Prints a binary tree in level order ($O(n)$).