Handwritten Notes on Data Structures and Algorithms

Data structures and algorithms form the bedrock of computer science and are essential tools for any aspiring programmer or developer. In this article, we present a unique and engaging approach to learning these fundamental concepts through Handwritten Notes on Data Structures and Algorithms. Combining the tactile experience of writing with the logical reasoning behind data structures and algorithms, these notes aim to provide a comprehensive understanding of the subject matter while catering to different learning styles.

The Power of Handwritten Notes:

Handwritten notes offer several advantages when it comes to learning complex subjects like data structures and algorithms. They engage both the visual and kinesthetic learning styles, allowing learners to absorb information through writing, reading, and seeing. Handwriting notes can also enhance memory retention and aid in better understanding and recall of concepts.

Fundamentals of Data Structures:

Introduction to Data Structures :

  1. Introduction
  2. Data and Information
  3. Elementary data structure organization
  4. Types of data structures
  5. Primitive and Non Primitive data structures

Operations on data structures :

  1. Traversing
  2. Inserting
  3. Deleting
  4. Searching
  5. Sorting
  6. Merging

Different Approaches to designing an algorithm :

  1. TopDown approach
  2. Bottom-up approach

Complexity :

  1. Time complexity
  2. Space
  3. complexity

Definition of a Stack:

  1. Operations on Stack (PUSH & POP)
  2. Implementing Push and Pop Operations Implementation of stack through arrays

Applications of Stack :

  1. Reversing a list
  2. Polish notations
  3. Conversion of infix to postfix expression
  4. Evaluation of postfix expression.

Recursion – Recursive definition:

  1. Properties of Recursive algorithms/functions
  2. Advantages and Disadvantages of Recursion
  3. Tower of Hanoi Problem.


  1. The queue and its representation
  2. implementation of Queues and their operations
  3. implementation of Circular queues and their operations
  4. Dequeue and Priority queues (Concepts only)

Linked List:

  1. Node
  2. Address
  3. Pointer
  4. Information
  5. Null Pointer

Empty list -Type of lists :

  1. Singly linked list
  2. Doubly linked list
  3. Circular list
  4. Representation of singly linked lists in Memory
  5. Difference between Linked & sequential List
  6. Advantages and Disadvantages of Linked list

Operations on a singly linked list (only algorithm) :

  1. Traversing a singly linked list
  2. Searching a singly linked list
  3. Inserting a new node in a singly linked list ( front, middle, end)
  4. Deleting a node from a singly linked list (front, middle, rear)
  5. Doubly linked list
  6. Circular linked lists (Concepts only, no implementations)

Trees: Data Structures


  1. Degree of a node
  2. degree of a tree
  3. level of a node
  4. leaf node
  5. Depth / Height of a tree
  6. In-degree & out-Degree
  7. Path
  8. Ancestor & descendant nodes
  9. siblings

Type of Trees :

  1. Binary tree
  2. List representation of Tree

Binary tree traversal:

  1. In order traversal
  2. Preorder traversal
  3. Post order traversal
  4. Binary Search Tree.

Graphs : Data Structures

Introduction – Terminologies:

  1. graph
  2. node (Vertices)
  3. arcs (edge)
  4. directed graph
  5. in-degree
  6. out-degree
  7. adjacent
  8. successor
  9. predecessor
  10. relation
  11. weight
  12. path
  13. length
  14. Representations of a graph
  15. Adjacency Matrix Representation
  16. Adjacency List Representation

Traversal of graphs :

  1. Depth-first search (DFS)
  2. Breadth-first search (BFS)
  3. Applications of Graph

Sorting Techniques :

Introduction – Algorithms and “C” programs for :

  1. Selection sort
  2. Insertion sort
  3. Bubble sort

Algorithms only :

  1. Merge Sort
  2. Radix sort
  3. Shell sort
  4. Quick sort.

Searching :

  1. Introduction – Algorithms and “C” programs for Linear search and Binary search


Handwritten notes provide a unique and effective approach to understanding data structures and algorithms. By combining the act of writing with the logical reasoning behind these concepts, learners can enhance their understanding, retention, and application of the subject matter. Whether you are a student, a professional, or simply passionate about programming, handwritten notes offer a valuable tool to master data structures and algorithms, empowering you to unlock endless possibilities in the world of computer science.
Remember, practice and implementation are key to solidifying your knowledge, so take these notes as a starting point and dive into coding exercises and real-world projects to further hone your skills. Happy learning!

(Note: This article provides a high-level overview of the topics covered. Further research and study are recommended for a deeper understanding of each concept.)

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