Knight’s Tour in C++: Warnsdorff’s Rule, Backtracking and a Tour Checker
A tested C++17 knight’s tour: Warnsdorff’s rule, backtracking for the cases it misses, and a checker that would have caught the old program’s bug.
Computer Science Tutorials — Algorithms, Data Structures, OOP and Programming Styles
Computer science is the intellectual foundation beneath every line of code you write. While programming teaches you how to instruct a computer, computer science teaches you why certain approaches work better than others — why one algorithm processes a million records in seconds while another takes hours, why the right data structure makes the difference between elegant and unworkable code, and why the principles of object-oriented design produce software that survives contact with the real world.
MYCPLUS has been publishing computer science tutorials and practical programming guides since 2004, building a comprehensive resource covering the core theoretical and applied topics that every serious programmer needs to understand. This Computer Science hub brings together four interconnected areas of study — Algorithms, Data Structures, Object-Oriented Programming and Programming Styles — each with its own dedicated section of in-depth tutorials, practical examples and working source code.
Tis section gives you the theoretical understanding and hands-on programming experience to write better software, solve harder problems and think more clearly about how programs work. Whether you are studying for exams, preparing for technical interviews or simply becoming a stronger programmer — start here.
What You’ll Learn
- Algorithms — sorting, searching, graph traversal, dynamic programming and optimisation techniques with working C implementations and complexity analysis for real-world problem solving
- Data structures — arrays, linked lists, stacks, queues, trees, hash tables and graphs with practical C and C++ source code examples and guidance on choosing the right structure for every problem
- Object-oriented programming — the complete OOP model including encapsulation, inheritance, polymorphism and abstraction with practical examples across C++, Java and C# for real-world software design
- Programming styles and paradigms — procedural, object-oriented, functional and declarative programming approaches with examples showing how modern developers apply multiple paradigms in professional codebases
- Algorithm complexity and analysis — understanding Big O notation, time and space complexity, best and worst case analysis and applying complexity thinking to write more efficient everyday code
- Applied computer science — bridging theory and practice by applying computer science principles to real programming problems in C, C++ and Java with source code you can study and build on immediately
Explore the four core areas covered in this section:
→ Algorithms — sorting, searching, graph traversal and optimisation
→ Data Structures — arrays, linked lists, trees, stacks and graphs
→ Object-Oriented Programming — classes, inheritance and polymorphism
→ Programming Styles — procedural, functional and declarative paradigms
Why MYCPLUS: Trusted by programmers and computer science students since 2004 — MYCPLUS covers all four core computer science disciplines in one place, with practical implementations in C, C++ and Java designed for both academic study and real-world software development.
Polymorphism in Object-Oriented Programming: Overloading, Overriding and Duck Typing in C++, Java and Python
How one call runs different code for different objects: overloading, overriding, virtual functions, generics and duck typing in C++, Java and Python.
Object-Oriented Programming: Concepts, Pillars and Techniques in C++, Java and Python
How OOP differs from procedural code, what its four pillars mean, and the techniques that keep object-oriented code easy to change, in three languages.
Objects in Object-Oriented Programming: Identity, State, Copying and Lifetime in C++, Java and Python
Why q = p1 copies an object in C++ but shares it in Java and Python, how equality differs from identity, and how each language ends an object’s life.
Abstraction in Object-Oriented Programming: Abstract Classes and Interfaces in C++, Java and Python
How abstract classes, interfaces and Python protocols separate what code does from how, with a testable clock example in C++, Java and Python.
Inheritance in Object-Oriented Programming: Types, Examples in C++, Java and Python, and When Not to Use It
One base class and two subclasses written in C++, Java and Python, the five types of inheritance, and why a subclass counted six tags when three were added.
Encapsulation in Object-Oriented Programming: Private State and Invariants in C++, Java and Python
How private state and checking methods keep an object valid, why a getter can leak it, and how Python gets encapsulation from properties and convention.
Classes in Object-Oriented Programming: Members, Constructors and Static Members in C++, Java and Python
One Temperature class written in C++, Java and Python, what a class stores once versus per object, and why a Python list in a class body was shared.
Towers of Hanoi: Recursive Algorithm With Code in C, C++, Java, Python and C#
Why the puzzle takes 2ⁿ − 1 moves, a timed 30-disk run, five tested implementations, and an iterative solver that computes any move directly.
Quicksort Algorithm — Lomuto vs Hoare, With Code in C, C++, Java, Python and C#
On 5,000 sorted values a last-element pivot makes 12.5 million comparisons instead of 67,000. Quicksort, measured — with code in five languages.
Shell Sort Algorithm: C, C++, Java, Python & C# Code
Shell Sort improves insertion sort by sorting far-apart elements first. See how it works, why gap sequences matter, and tested code in five languages.
Merge Sort in C, C++, Java, Python and C#: Top-Down, Bottom-Up and Linked Lists
Merge sort is stable and O(n log n) on every input. Code in five languages, measured comparisons and allocations, and four mistakes that compile.