This repository contains C# programming fundamentals, algorithms, data structures, and OOP concepts. Each section is structured to cover key topics comprehensively, ensuring a smooth learning path from basic syntax to advanced algorithms and design patterns in C#.
ProgrammingInCSharp/
├── 01-Introduction-to-Programming/
│ ├── BasicSyntax.cs
│ ├── ControlStructures.cs
│ └── VariablesAndDataTypes.cs
├── 02-OOPs/
│ ├── ClassesAndObjects.cs
│ ├── InheritanceExample.cs
│ ├── OOP-Concepts.md
│ └── PolymorphismExample.cs
├── 03-Searching-Algorithms/
│ ├── BinarySearch.cs
│ ├── LinearSearch.cs
│ ├── SearchTimeComparison.cs
│ └── SearchingComplexityAnalysis.md
├── 04-Sorting-Algorithms/
│ ├── BubbleSort.cs
│ ├── MergeSort.cs
│ ├── QuickSort.cs
│ └── SortingPerformanceAnalysis.md
├── 05-BigO-Notation/
│ ├── BigOExamples.cs
│ └── BigOExplanation.md
├── 06-Data-Structures/
│ ├── Arrays/
│ │ └── ArraysBasics.cs
│ ├── Dictionaries/
│ │ └── DictionaryOperations.cs
│ └── Strings/
│ └── StringManipulation.cs
├── 07-Algorithms/
├── DivideAndConquer/
│ └── MergeSort.cs
├── DynamicProgramming/
│ └── KnapsackProblem.cs
└── Recursion/
└── Fibonacci.cs
- Topics to Cover:
- Variables and Data Types (
int,double,string,bool) - Basic arithmetic operations
- Simple method creation and usage
- Console I/O (
Console.ReadLine(),Console.WriteLine()) - Comments and code structure
- Variables and Data Types (
- Objective: Provide an introduction to the syntax and fundamentals of C# programming.
- Topics to Cover:
- Conditional statements:
if,else if,else - Switch-case statements
- Loops:
forloopwhileloopdo-whileloop
- Nested control structures
- Break and continue statements
- Conditional statements:
- Objective: Teach how to control the flow of a C# program through conditionals and loops.
- Topics to Cover:
- Variable scope and lifetime (local and global variables)
- Constants and
readonlyvariables - Enumerations (
enum) - Typecasting and conversions (
Convert.ToInt32(),int.Parse(), explicit/implicit casting) - Nullable types
- Objective: Expand on data types, variable handling, type conversion, and nullable types.
- Topics to Cover:
- Defining classes and creating objects
- Fields, properties, methods, and constructors
- Object instantiation and method calls
- Objective: Provide a comprehensive introduction to classes and objects in C#.
- Topics to Cover:
- Inheritance in C# (base and derived classes)
- Method overriding
protectedaccess modifier
- Objective: Teach inheritance, method overriding, and code reuse through inheritance.
- Topics to Cover:
- Polymorphism in C#
- Method overloading and overriding
- Use of
virtualandoverridekeywords - Dynamic (run-time) polymorphism using interfaces or base classes
- Objective: Demonstrate polymorphism and its applications in making code flexible and reusable.
- Topics to Cover:
- Binary Search algorithm (recursive and iterative versions)
- Pre-requisite: sorted array
- Time complexity analysis (
O(log n))
- Objective: Demonstrate efficient searching in a sorted array using Binary Search.
- Topics to Cover:
- Linear Search algorithm
- Code implementation and use cases
- Time complexity (
O(n))
- Objective: Provide a simple implementation of Linear Search, comparing it to Binary Search.
- Topics to Cover:
- Compare search times: Linear Search, Binary Search, and Dictionary Search.
- Time measurement using
Stopwatchclass. - Analyze time complexity differences and practical performance.
- Objective: Demonstrate search time comparison for
O(n),O(log n), andO(1)searches across data structures.
- Content:
- Compare the time complexity of Binary Search and Linear Search.
- Discuss when each algorithm is appropriate.
- Examples of real-world scenarios for each.
- Objective: Analyze the performance of searching algorithms based on array properties.
- Topics to Cover:
- Bubble Sort algorithm (step-by-step explanation)
- Code implementation of Bubble Sort
- Time complexity analysis (
O(n^2))
- Objective: Implement and explain Bubble Sort, focusing on its simplicity and inefficiency for large data sets.
- Topics to Cover:
- Quick Sort algorithm (recursive partitioning)
- Code implementation with pivot selection and recursive sorting
- Time complexity analysis (
O(n log n)best case,O(n^2)worst case)
- Objective: Introduce and explain Quick Sort, including its efficiency compared to Bubble Sort.
- Topics to Cover:
- Merge Sort algorithm (divide and conquer)
- Recursive code implementation
- Merging sorted subarrays
- Time complexity (
O(n log n))
- Objective: Provide a divide-and-conquer approach to sorting.
- Content:
- Compare time and space complexity of Bubble Sort, Quick Sort, and Merge Sort.
- When to use each algorithm.
- Practical performance insights based on input size and array structure.
- Objective: Offer a detailed performance comparison and guidance on algorithm selection.
- Content:
- Explanation of Big O notation
- Common time complexities (
O(1),O(n),O(log n),O(n^2)) - Examples of each complexity (e.g., constant time for access, linear time for loops, logarithmic time for binary search)
- Objective: Provide a theoretical explanation of Big O notation and time complexity.
- Topics to Cover:
- Practical code examples demonstrating each time complexity:
O(1)for constant time (e.g., accessing an array element)O(n)for linear time (e.g., traversing a list)O(log n)for logarithmic time (e.g., binary search)O(n^2)for quadratic time (e.g., nested loops)
- Practical code examples demonstrating each time complexity:
- Objective: Implement real-world examples of different Big O complexities.
- Topics to Cover:
- Array declaration, initialization, and access
- Single-dimensional and multi-dimensional arrays
- Jagged arrays
- Array traversal (for and foreach)
- Array methods (
Array.Sort(),Array.Reverse())
- Objective: Introduce arrays and how to manipulate them in various ways.
- Topics to Cover:
- String declaration and initialization
- Common string methods (
Substring(),Replace(),IndexOf(),Trim(), etc.) - String interpolation and concatenation
- String comparison (
CompareTo(),Equals()) - String immutability
- Objective: Demonstrate how to manipulate strings in C# and explain string immutability.
- Topics to Cover:
- Dictionary declaration and initialization
- Adding, removing, and updating dictionary elements
- Key-based lookup (
TryGetValue()) - Iterating through dictionaries (
foreach) - Dictionary performance considerations
- Objective: Provide a comprehensive introduction to dictionaries and their uses.
- Topics to Cover:
- Fibonacci sequence using recursion and iteration
- Time complexity analysis (recursive version: exponential time
O(2^n)) - Memoization to optimize recursive Fibonacci (
O(n))
- Objective: Teach recursion with Fibonacci and optimize it using memoization.
- Topics to Cover:
- Recap of Merge Sort from
Sorting Algorithms - Explanation of the divide-and-conquer paradigm (dividing a problem into subproblems)
- Recap of Merge Sort from
- Objective: Reinforce the divide-and-conquer strategy using Merge Sort.
- Topics to Cover:
- 0/1 Knapsack Problem using dynamic programming
- Bottom-up approach and memoization
- Time complexity analysis (
O(nW))
- Objective: Provide a deep dive into dynamic programming using the Knapsack Problem.
The following path is designed to progressively enhance your understanding of C# from fundamental concepts to advanced programming techniques.
-
Start with Programming Fundamentals:
- Introduction to Programming:
- Basic Syntax, Control Structures, and Variables & Data Types will establish a strong foundation for programming in C#.
- Introduction to Programming:
-
Explore Object-Oriented Programming (OOP):
- Classes and Objects, Inheritance, and Polymorphism are key OOP principles.
- Learn to implement these concepts in C# to build modular and reusable code.
-
Move to Data Structures:
- Start with Arrays
- This section introduces common data structures and their manipulation, providing the tools needed for effective data handling.
-
Study Sorting and Searching Algorithms:
- Implement and compare common algorithms like Bubble Sort, Quick Sort, Merge Sort, and searching techniques like Binary Search and Linear Search.
- The Search Time Comparison section will offer practical insights into real-world performance.
-
Understand Algorithm Complexity with Big O:
- Big O Notation will help you understand the time and space complexities of algorithms.
- Real-world examples will solidify your ability to evaluate algorithm performance.
-
Move to Data Structures:
- Learn about Dictionaries, Strings
-
Deepen your Knowledge of Advanced Algorithms:
- Study Recursion, Divide and Conquer techniques like Merge Sort, and Dynamic Programming with the Knapsack Problem.
This path will ensure you gradually develop from basic to advanced C# programming skills, helping you master the language through a structured approach.
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Harsha Sai Jagu