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docs/extra/Banker's Algorithm/Banker.md

@@ -2,8 +2,15 @@
 id: banker's-algorithm
 title: Banker's Algorithm
 sidebar_label: Banker's Algorithm
-description: "It is a method used to avoid deadlocks in a system by checking if there exists a safe sequence of resource allocation for processes using safety checks based on available resources."
-tags: [operating systems, algorithms, deadlock prevention]
+description: >-
+  It is a method used to avoid deadlocks in a system by checking if there exists
+  a safe sequence of resource allocation for processes using safety checks based
+  on available resources.
+tags:
+  - operating systems
+  - algorithms
+  - deadlock prevention
+sidebar_position: 1
 ---
 
 The Banker's Algorithm is a deadlock avoidance algorithm used in operating systems. It allocates resources to processes in a safe manner by verifying that the system can allocate resources in a way that avoids deadlocks. It ensures a "safe state" where resources can be allocated without risk of deadlock, based on maximum and current allocations.
@@ -234,4 +241,4 @@ else:
 
 ### Summary:
 
-The Banker's Algorithm is crucial for systems requiring deadlock avoidance in resource allocation. By dynamically checking if resources can be safely allocated without risking deadlock, it helps maintain system stability, making it widely used in operating system designs.
+The Banker's Algorithm is crucial for systems requiring deadlock avoidance in resource allocation. By dynamically checking if resources can be safely allocated without risking deadlock, it helps maintain system stability, making it widely used in operating system designs.

docs/extra/Circular_array/Introduction.md

@@ -1,10 +1,10 @@
 ---
 id: circular-array-introduction
 sidebar_position: 1
-title: Introduction of Circular
+title: Introduction to Circular Array
 sidebar_label: Introduction
-description: "A B-tree is a self-balancing tree data structure that maintains sorted data for efficient insertion, deletion, and search operations."
-tags: [b-tree, algorithms, problem-solving, DSA, data structure]
+description: "An introduction to Circular Arrays (circular buffers), their key features, use cases, complexity analysis, and implementations in Python, Java, and C++."
+tags: [circular-array, data-structures, arrays, algorithms]
 ---
 
 ## Introduction

docs/extra/Divide and Conquer/Maximum-minimum.md

@@ -2,8 +2,14 @@
 id: maximum-minimum
 title: Maximum-minimum
 sidebar_label: Maximum-minimum
-description: "Maximum minimum finding using divide and conquer approach to reduce the number of comparisions."  
-tags: [dsa, algorithms, divide and conquer]
+description: >-
+  Maximum minimum finding using divide and conquer approach to reduce the number
+  of comparisions.
+tags:
+  - dsa
+  - algorithms
+  - divide and conquer
+sidebar_position: 2
 ---
 
 ### Definition:

docs/extra/Divide and Conquer/Strassen's-Matrix-Mutiplication.md

@@ -1,9 +1,15 @@
 ---
 id: strassens-matrix-mutiplication
 title: Strassen's-Matrix-Mutiplication
-sidebar_label: Strassen's-Matrix-Mutiplication 
-description: "Strassen's matrix multiplication is an efficient algorithm that reduces the time complexity of multiplying two matrices."  
-tags: [dsa, algorithms, divide and conquer]
+sidebar_label: Strassen's-Matrix-Mutiplication
+description: >-
+  Strassen's matrix multiplication is an efficient algorithm that reduces the
+  time complexity of multiplying two matrices.
+tags:
+  - dsa
+  - algorithms
+  - divide and conquer
+sidebar_position: 3
 ---
 
 ### Problem Statement:

docs/extra/Divide and Conquer/convex-hull.md

@@ -1,9 +1,15 @@
 ---
 id: convex-hull
-title: "Convex Hull Problem"
-sidebar_label: "Convex Hull"
-description: "This document provides an overview of the Convex Hull problem using the divide-and-conquer approach."
-tags: [divide-and-conquer, computational-geometry, algorithms]
+title: Convex Hull Problem
+sidebar_label: Convex Hull
+description: >-
+  This document provides an overview of the Convex Hull problem using the
+  divide-and-conquer approach.
+tags:
+  - divide-and-conquer
+  - computational-geometry
+  - algorithms
+sidebar_position: 1
 ---
 
 <AdsComponent />

docs/extra/Hashing/CollisionHandling.md

@@ -3,7 +3,12 @@ id: collision-handling-in-hashing
 sidebar_position: 5
 title: Collision Handling in Hashing
 sidebar_label: Collision Handling in Hashing
-tags: [hashing, data structures]
+tags:
+  - hashing
+  - data structures
+description: >-
+  Detailed guide on Collision Handling in Hashing including core concepts,
+  algorithmic implementation, complexity analysis, and practice problems.
 ---
 
 # Collision Handling in Hashing

docs/extra/Hashing/Tigerhashing.md

@@ -1,3 +1,17 @@
+---
+id: tigerhashing
+title: Tiger Hashing Algorithm
+sidebar_label: Tiger Hashing Algorithm
+description: >-
+  Detailed guide on Tiger Hashing Algorithm including core concepts, algorithmic
+  implementation, complexity analysis, and practice problems.
+tags:
+  - programming
+  - dsa
+  - hashing
+  - tiger hashing algorithm
+sidebar_position: 8
+---
 # Tiger Hashing Algorithm
 
 ## Overview

docs/extra/Jump Search/Jump Search.md

@@ -2,8 +2,13 @@
 id: jump-search
 title: Jump Search Algorithm
 sidebar_label: Jump Search
-description: "This post explores the use of Jump Search Algorithm. We'll provide code implementations C++."
-tags: [searching, algorithms]
+description: >-
+  This post explores the use of Jump Search Algorithm. We'll provide code
+  implementations C++.
+tags:
+  - searching
+  - algorithms
+sidebar_position: 1
 ---
 
 Jump Search is a searching algorithm used to find an element in a sorted array. It works by jumping ahead by a fixed number of steps, rather than checking each element one by one (as in linear search). Once it finds an interval where the target element might be, it performs a linear search within that interval.

docs/extra/KMP searching pattern/readme.md

@@ -2,8 +2,16 @@
 id: kmp-searching-pattern
 title: KMP Pattern Searching Algorithm - Complete Guide
 sidebar_label: KMP Pattern Searching
-description: A comprehensive guide to the Knuth-Morris-Pratt (KMP) string matching algorithm, including theory, analysis, and implementations in multiple languages
-tags: [Algorithms, String Matching, Pattern Searching, Dynamic Programming]
+description: >-
+  A comprehensive guide to the Knuth-Morris-Pratt (KMP) string matching
+  algorithm, including theory, analysis, and implementations in multiple
+  languages
+tags:
+  - Algorithms
+  - String Matching
+  - Pattern Searching
+  - Dynamic Programming
+sidebar_position: 1
 ---
 
 # 🔍 KMP (Knuth-Morris-Pratt) Pattern Searching Algorithm

docs/extra/Object Oriented Programming/Polymorphism.md

@@ -1,10 +1,13 @@
 ---
 id: Polymorphism
-title: "Polymorphism in Object-Oriented Programming"
-sidebar_label: "Generate Details about Polymorphism"
-description: "
-Polymorphism is a core concept in object-oriented programming that allows objects of different classes to be treated as instances of the same class through a shared interface"
-tags: [Polymorphism, OOPS, Java]
+title: Polymorphism in Object-Oriented Programming
+sidebar_label: Generate Details about Polymorphism
+description: ' Polymorphism is a core concept in object-oriented programming that allows objects of different classes to be treated as instances of the same class through a shared interface'
+tags:
+  - Polymorphism
+  - OOPS
+  - Java
+sidebar_position: 8
 ---
 
 ## Polymorphism

docs/extra/Object Oriented Programming/abstraction.md

@@ -1,9 +1,15 @@
 ---
 id: abstraction
-title: "Abstraction in Object-Oriented Programming"
-sidebar_label: "Generate Details about Abstraction"
-description: "Abstraction in Java is the process of hiding unnecessary implementation details from the user, focusing on exposing only the essential functionalities"
-tags: [Abstraaction, OOPS, Java]
+title: Abstraction in Object-Oriented Programming
+sidebar_label: Generate Details about Abstraction
+description: >-
+  Abstraction in Java is the process of hiding unnecessary implementation
+  details from the user, focusing on exposing only the essential functionalities
+tags:
+  - Abstraaction
+  - OOPS
+  - Java
+sidebar_position: 2
 ---
 
 <AdsComponent />

docs/extra/Object Oriented Programming/classes-and-objects.md

@@ -1,5 +1,5 @@
 ---
-id: classes-and-objects
+id: classes-and-objects-oop
 title: "Classes and Objects in OOP"
 sidebar_label: Classes and Objects
 sidebar_position: 2

docs/extra/Queue/Problem-Practice.md

@@ -3,8 +3,17 @@ id: Practice-Problems-on-queue
 title: Queue Practice Problems
 sidebar_label: Queue Practice Problems
 sidebar_position: 9
-Description: Here are some practice problems for queuing data structure divided into topic and width.
-tags: [DSA, algorithms, Queue, dsa]
+Description: >-
+  Here are some practice problems for queuing data structure divided into topic
+  and width.
+tags:
+  - DSA
+  - algorithms
+  - Queue
+  - dsa
+description: >-
+  Detailed guide on Queue Practice Problems including core concepts, algorithmic
+  implementation, complexity analysis, and practice problems.
 ---
 
 ### Basic Queue Problems:

docs/extra/Randomized Algorithm/Randomized-Quicksort.md

@@ -2,8 +2,14 @@
 id: randomized-quicksort
 title: Randomized Quick Sort
 sidebar_label: Randomized Quick Sort
-description: "Randomized quicksort is a sorting algorithm that is an extension of quicksort, but with a random pivot selection"  
-tags: [dsa, algorithms, sorting]
+description: >-
+  Randomized quicksort is a sorting algorithm that is an extension of quicksort,
+  but with a random pivot selection
+tags:
+  - dsa
+  - algorithms
+  - sorting
+sidebar_position: 1
 ---
 
 ### Problem Statement:

docs/extra/Recursion-depths/Recursion.md

@@ -1,7 +1,7 @@
 ---
 id: recursion-depth-overview
 title: Recursion Depth Overview
-sidebar_label: Overview
+sidebar_label: Recursion Depth
 sidebar_position: 5
 description: An overview of recursion depth and its role in recursive algorithms.
 tags: [recursion, algorithms, depth]

docs/extra/Recursion/Ackerman.md

@@ -1,9 +1,22 @@
 ---
-id: ackerman-function 
+id: ackerman-function
 title: Ackerman Function Using Recursion
-sidebar_label: Generate Ackerman Function value 
-description: "The Ackermann function is a recursive function that grows incredibly fast and is often used to demonstrate the power and limitations of recursion. Defined with two arguments,m and n, it exhibits rapid growth even for small inputs, making it a classic example in theoretical computer science. Unlike simpler recursive functions, it is non-primitive recursive, meaning it cannot be expressed using basic loops. This function challenges computational limits, often exceeding recursion stack sizes in practical programming environments. Its main use is in studying recursion, computability, and the limits of algorithms."
-tags: [Ackerman , recursion, dsa]
+sidebar_label: Generate Ackerman Function value
+description: >-
+  The Ackermann function is a recursive function that grows incredibly fast and
+  is often used to demonstrate the power and limitations of recursion. Defined
+  with two arguments,m and n, it exhibits rapid growth even for small inputs,
+  making it a classic example in theoretical computer science. Unlike simpler
+  recursive functions, it is non-primitive recursive, meaning it cannot be
+  expressed using basic loops. This function challenges computational limits,
+  often exceeding recursion stack sizes in practical programming environments.
+  Its main use is in studying recursion, computability, and the limits of
+  algorithms.
+tags:
+  - Ackerman
+  - recursion
+  - dsa
+sidebar_position: 1
 ---
 ## Ackerman Function Via Recursion
 

docs/extra/Recursion/Count-all-subsequences-with-sum-K.md

@@ -2,8 +2,17 @@
 id: count-all-subsequences-with-sum-k-problem-dsa
 title: Perfect sum
 sidebar_label: Perfect sum
-description: "The Perfect Sum problem involves finding all subsets of an array that sum up to a given target sum. The solution uses recursion and dynamic programming to efficiently count subsets with a specified sum while handling large values using modulo."
-tags: [perfect-sum, recursion, dynamic-programming, dsa]
+description: >-
+  The Perfect Sum problem involves finding all subsets of an array that sum up
+  to a given target sum. The solution uses recursion and dynamic programming to
+  efficiently count subsets with a specified sum while handling large values
+  using modulo.
+tags:
+  - perfect-sum
+  - recursion
+  - dynamic-programming
+  - dsa
+sidebar_position: 3
 ---
 
 ## Perfect Sum Problem | Count All Subsets with Sum k

docs/extra/Recursion/GrayCodeGeneration.md

@@ -2,8 +2,12 @@
 id: Gray Code Generation
 title: Gray Code Generation Using Recursion
 sidebar_label: Generate Gray Code
-description: "Gray code generation is a process of creating a sequence of binary numbers in which two successive values differ in only one bit. This unique property is useful in various applications, such as minimizing errors in digital communication and ensuring smooth transitions in analog-to-digital converters. The generation can be efficiently achieved using a recursive algorithm, which constructs Gray codes for 𝑛 by leveraging the codes generated for 𝑛−1 bits. The resulting Gray code sequences maintain a structured format, making them ideal for error detection and correction in digital systems"
-tags: [Gray-Code, recursion, dsa]
+description: "Gray code generation is a process of creating a sequence of binary numbers in which two successive values differ in only one bit. This unique property is useful in various applications, such as minimizing errors in digital communication and ensuring smooth transitions in analog-to-digital converters. The generation can be efficiently achieved using a recursive algorithm, which constructs Gray codes for \U0001D45B by leveraging the codes generated for \U0001D45B−1 bits. The resulting Gray code sequences maintain a structured format, making them ideal for error detection and correction in digital systems"
+tags:
+  - Gray-Code
+  - recursion
+  - dsa
+sidebar_position: 6
 ---
 
 ## Gray Code Generation Via Recursion

docs/extra/Recursion/Letter-Combinations-of-a-Phone-number.md

@@ -2,8 +2,17 @@
 id: Letter-Combinations-problem-dsa
 title: Letter Combinations of a Phone Number
 sidebar_label: Letter Combinations
-description: "The Letter Combinations of a Phone Number problem involves generating all possible letter combinations that a string of digits (2-9) can represent based on a standard telephone keypad. This problem is often solved using recursion and backtracking."
-tags: [letter-combinations, backtracking, recursion, dsa]
+description: >-
+  The Letter Combinations of a Phone Number problem involves generating all
+  possible letter combinations that a string of digits (2-9) can represent based
+  on a standard telephone keypad. This problem is often solved using recursion
+  and backtracking.
+tags:
+  - letter-combinations
+  - backtracking
+  - recursion
+  - dsa
+sidebar_position: 10
 ---
 
 ## Letter Combinations of a Phone Number | Generate All Combinations of Letters Based on Digits

docs/extra/Recursion/Reversing_String.md

@@ -2,8 +2,15 @@
 id: reverse-string-recursion
 title: Reverse String Using Recursion
 sidebar_label: Reverse String
-description: "The Reverse String problem involves reversing a given string using a recursive function. The solution efficiently utilizes recursion to achieve the desired result without using any iterative constructs."
-tags: [reverse-string, recursion, dsa]
+description: >-
+  The Reverse String problem involves reversing a given string using a recursive
+  function. The solution efficiently utilizes recursion to achieve the desired
+  result without using any iterative constructs.
+tags:
+  - reverse-string
+  - recursion
+  - dsa
+sidebar_position: 14
 ---
 
 ## Reverse String Using Recursion
@@ -79,4 +86,4 @@ public class Solution {
         System.out.println("Reversed string: " + solution.reverseString(str));
     }
 }
-```
+```

docs/extra/Recursion/SmawkAlgorithm.md

@@ -1,9 +1,22 @@
 ---
-id: smawk-algorithm 
+id: smawk-algorithm
 title: Smawk Algorithm Using Recursion
-sidebar_label: Generating Minima in matrix row  
-description: "The SMAWK algorithm is an efficient method for finding row minima in totally monotone matrices, a specific type of matrix where entries decrease or stay constant along each row and column. Developed for optimizing complex search operations, this algorithm leverages a unique recursive approach, reducing computation time to O(m+n) for an m×n matrix, making it ideal for applications in computational geometry, dynamic programming, and machine learning. With SMAWK, developers gain a powerful tool for solving matrix-based problems more effectively, significantly improving the performance of algorithms that depend on finding minimum values in large, structured datasets"
-tags: [Smawk , recursion, dsa]
+sidebar_label: Generating Minima in matrix row
+description: >-
+  The SMAWK algorithm is an efficient method for finding row minima in totally
+  monotone matrices, a specific type of matrix where entries decrease or stay
+  constant along each row and column. Developed for optimizing complex search
+  operations, this algorithm leverages a unique recursive approach, reducing
+  computation time to O(m+n) for an m×n matrix, making it ideal for applications
+  in computational geometry, dynamic programming, and machine learning. With
+  SMAWK, developers gain a powerful tool for solving matrix-based problems more
+  effectively, significantly improving the performance of algorithms that depend
+  on finding minimum values in large, structured datasets
+tags:
+  - Smawk
+  - recursion
+  - dsa
+sidebar_position: 15
 ---
 ## Smawk Algorithm Via Recursion