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.
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.
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.
Insertion Sort in C, C++, Java, Python and C#: How It Works and What It Costs
Insertion sort moves one element per out-of-order pair. A traced example, code in five languages, and measurements that show what that costs.
Bubble Sort in C and C++: Step-by-Step Passes, Early Exit and Complexity
Bubble sort explained with a pass table, clean C and C++ code, measured comparison counts, and when qsort or std::sort is the better choice.
Selection Sort in C, C++, Java, Python and C#: Swaps, Stability and Speed
Selection sort always makes n(n − 1)/2 comparisons and at most n − 1 swaps. Code in five languages, measured counts, and three mistakes that sort.
Heap Sort in C, C++, Java, Python and C#: Heaps, Sift-Down and Real Costs
Heap sort is O(n log n) in place on every input. How the heap lives in an array, code in five languages, and what the guarantee costs against quicksort.
Sorting Algorithms in C and C++: Complexity, Stability and Measured Comparisons
Complexity, stability and measured comparison counts for seven sorting algorithms, plus qsort, std::sort and std::stable_sort on the same data.
Knapsack Problem in C and C++: 0/1 Dynamic Programming, Item Recovery and the Fractional Variant
0/1 knapsack in C and C++: the DP recurrence, item recovery, why greedy and an upward loop give wrong answers, and the fractional variant, all tested.
Stack Implementation in C, C++, Java, Python and C#: Arrays, Linked Lists and the Standard Library
Stacks in five languages, built two ways and measured: memory per element, reallocations per million pushes, empty-pop behaviour and four common bugs.
Prime Number Program in C, C++, Java, Python, C#, PHP and JavaScript
A square-root primality test, the Sieve of Eratosthenes and Miller–Rabin in seven languages, with the four bugs that pass a quick test.
Arrays as a Data Structure in C and C++
An array is a fixed block of memory that does not know its own length. Everything else about using one in C and C++ follows from those two facts.
Top 10 Algorithms Every Programmer Should Know (With Code and Complexity)
At n = 1,000,000, O(log n) takes 20 steps and O(n squared) takes a trillion. The ten families that matter, with complexity for each.