Module 1: Introduction to Data Structures and Algorithms

• Educational Goal: To introduce the fundamental concepts of data structures and algorithms, their importance in computer science, and the relationship between them.
• Topics:
  • Definition of data structures and algorithms
  • Importance of data structures in computer science
  • Algorithm design and analysis (time and space complexity)
  • Abstract data types (ADTs)

Module 2: Primitive Data Types and Data Representation

• Educational Goal: To understand the basic building blocks of data structures and how they are represented in computer memory.
• Topics:
  • Primitive data types (integers, floating-point numbers, characters, booleans)
  • Data representation in memory (binary, hexadecimal, two’s complement)
  • Bitwise operations
  • Character encoding (ASCII, Unicode)

Module 3: Arrays and Strings

• Educational Goal: To understand the concept of arrays, their different types, and how they are used to store and manipulate collections of data.
• Topics:
  • Arrays (one-dimensional, multi-dimensional, jagged arrays)
  • Array operations (searching, sorting, insertion, deletion)
  • Strings as arrays of characters
  • String manipulation algorithms (substring, concatenation, searching)

Module 4: Records and Structures

• Educational Goal: To understand how to group related data items together using records (or structures) and their applications.
• Topics:
  • Records (or structures) as collections of different data types
  • Accessing and modifying fields within records
  • Applications of records (e.g., representing employee data, student records)
  • Unions (data structures that can hold values of different types)

Module 5: Pointers and References

• Educational Goal: To understand the concept of pointers and references, their role in memory management, and their use in implementing dynamic data structures.
• Topics:
  • Memory addresses and pointers
  • Pointer arithmetic and operations
  • Pass-by-reference vs. pass-by-value
  • Dynamic memory allocation (malloc, free)
  • Dangling pointers and memory leaks

Module 6: Linked Lists

• Educational Goal: To understand the concept of linked lists, their different types, and their applications in various data structures.
• Topics:
  • Singly linked lists
  • Doubly linked lists
  • Circular linked lists
  • Linked list operations (insertion, deletion, traversal)
  • Applications of linked lists (e.g., implementing stacks, queues)

Module 7: Stacks, Queues, and Trees

• Educational Goal: To understand the concepts of stacks, queues, and trees, their characteristics, and their implementations using arrays and linked lists.
• Topics:
  • Stacks (LIFO) and their applications (e.g., function calls, expression evaluation)
  • Queues (FIFO) and their applications (e.g., scheduling, breadth-first search)
  • Trees (binary trees, binary search trees)
  • Tree traversal algorithms (in-order, pre-order, post-order)

Module 8: Hashing and Graphs

• Educational Goal: To understand the concepts of hashing, graph data structures, and their applications in various domains.
• Topics:
  • Hashing functions and hash tables
  • Collision resolution techniques (chaining, open addressing)
  • Graphs (directed, undirected, weighted)
  • Graph traversal algorithms (depth-first search, breadth-first search)
  • Applications of graphs (e.g., social networks, transportation networks)

Teaching Methods:

• Lectures
• Hands-on coding exercises and assignments
• Problem-solving sessions
• Group projects
• Class discussions and debates

Assessment:

• Assignments (coding exercises, problem-solving assignments)
• Quizzes and exams
• Midterm exam
• Final project (implementing a data structure or algorithm)
• Class participation

Basic Cornerstone

Program = Algorithm + Data Structure

Balanced tree

• All empty links are located on the last row
• Capacity of a binary tree: \(b^n - 1\)
• 3 rows of a binary tree: \(2^3 - 1\)

Recursive printing of a Binary tree

def printtree(root)
   if !root.leftlink.nil? 
        printtree(root.leftlink)
     end
     puts root.data
     if !root.rightlink.nil?
       printtree(root.leftlink)
     end
end

A Hamilton path

(Only works when you start and end on the vertices with odd number of edges. Only two or less vertices with odd numbered edges are permitted)

A hamilton circuit:

Works from any starting point and always ends up at the starting point.