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.
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.
Originally written in 1979 at Computer Laboratory, Cambridge (England), it was reprinted in 1997 in the book “Readings in Information Retrieval”. Initially it was written in BCPL language. Here is the list of implementations in other programming languages including C, Java and Pearl implementations done by author himself.
These algorithms are represented in terms of compact implementations in C so that readers can both understand their fundamental properties and implement them in real applications. The method of the analysis of algorithms is quite carefully designed. When appropriate, analytic results are described to explain why certain algorithms are preferred. In some cases, the practical algorithms’ relationship being discussed to purely theoretical results is also described.
A binary tree is made of nodes, where each node contains a “left” pointer, a “right” pointer, and a data
As discussed in our previous post, C and C++ programmers have access to two main types of data structures: built-in
The basic aim of mycplus.com website was to develop a website for students of C/C++ and data structures. There are lots of tutorials and source code covering different aspects of C/C++ programming language. Today I have decided to write few articles about data structures and their implementation in C/C++.
Master cybersecurity with Applied Cryptography! Explore protocols, algorithms, and real-world applications in this must-have guide for tech professionals and enthusiasts. Get your copy now!
Master efficient coding with Data Structures and Algorithm Analysis in C++ – your ultimate guide to building high-performance software solutions!
Delve into the fundamentals of data structures and algorithms with Data Structures and Algorithm Analysis in Java. This comprehensive guide focuses on performance optimization, scalability, and real-world Java implementations. From sorting to dynamic programming, it equips developers with the tools to build efficient, high-performance applications. A must-read for students and professionals seeking to master Java’s capabilities in solving complex computational problems.
This is a short document describing the preferred coding style for the Linux kernel. Coding style is very personal, and I won’t _force_ my views on anybody, but this is what goes for anything that I have to be able to maintain, and I’d prefer it for most other things too. Please at least consider the points made here.
This document is a result of a committee formed at Indian Hill to establish a common set of coding standards and recommendations for the Indian Hill community. The scope of this work is the coding style, not the functional organization of programs. The standards in this document are not specific to ESS programming only.
Reference standards Don’t in any circumstances refer to Unix source code for or during your work on GNU! (Or to
Polymorphism lets a single method call take many forms. This practical guide explains compile-time vs runtime polymorphism and walks through runnable C++, Java, and Python examples you can try right away.
