Computer Programming Algorithms

Discover the Trie, a specialised tree for string operations. Learn how Auto-Complete works and how to search a dictionary of words in O(L) time.

The crown jewel of pathfinding. Learn how A* combines Dijkstra's guaranteed accuracy with a Greedy Best-First Search heuristic to find the shortest path lightning-fast.

Zoom down to the 1s and 0s. Master Bitwise AND, OR, XOR, and Shifts to solve problems with brutal efficiency and zero memory overhead.

Demystify Recursion. Learn how functions call themselves, how the Call Stack unwinds, and the difference between Head Recursion and Tail Recursion.

Learn how to solve Sudoku, N-Queens, and combination puzzles using Backtracking. We cover the core template that solves almost all combinatorial search problems.

Why look at the big picture when you can just make the best immediate choice? Learn when Greedy Algorithms work, and more importantly, when they fail.

Master Bottom-Up Dynamic Programming. Learn how to replace recursive Memoization with iterative Tabulation to eliminate StackOverflows and optimise memory.

Unlock the power of Top-Down Dynamic Programming. Learn how Memoization turns slow $O(2^n)$ recursive algorithms into lightning-fast $O(n)$ solutions.

Master Dijkstra's algorithm to find the absolute shortest path on weighted graphs. Learn how it combines BFS and a Priority Queue to work its magic.

Master Depth-First Search for graphs. Learn how to implement DFS recursively and iteratively to detect cycles, find connected components, and solve mazes.

Enter the world of Graphs. Learn how to represent graphs using Adjacency Lists and Matrices, and master Breadth-First Search (BFS) to find the shortest paths.

Master Heaps and Priority Queues. Discover how an array can represent a perfect binary tree, and how to get the maximum or minimum element in O(1) time.

Learn how Binary Search Trees achieve O(log n) lookups by enforcing strict ordering rules. Includes Java implementation of insert, search, and delete operations.

Discover the anatomy of Binary Trees. Learn the four main traversal methods (In-order, Pre-order, Post-order, Level-order) with clear diagrams and Java code.

Everything you need to know about Linked Lists. Learn how nodes connect via pointers, difference between Singly and Doubly linked lists, and Java implementation.

Understand the magic behind O(1) lookups. We explain Hash Tables, Hash Functions, and collision resolution techniques with Java's HashMap.

Learn the core concepts of Stacks (LIFO) and Queues (FIFO). Understand their operations, time complexities, and see them implemented in Java using Deque.

Master the Sliding Window technique to solve contiguous sub-array and sub-string problems efficiently. Covers fixed-size and dynamic window patterns with Java examples.

Learn the Two Pointer technique to solve array and string problems efficiently. Covers opposite-direction and same-direction patterns with Java examples.

Master the two fundamental search algorithms. From the brute-force scan of Linear Search to the elegant halving strategy of Binary Search, with Java code and traced examples.

Break the O(n log n) barrier with linear-time sorting algorithms. Learn how Counting Sort, Radix Sort, and Bucket Sort work with detailed examples and Java code.

Discover how Quick Sort partitions arrays around a pivot to achieve O(n log n) average performance in-place. Full Java code, traced example, and pivot strategy discussion.

Master Merge Sort with a visual divide-and-conquer walkthrough, complete Java implementation, and a deep dive into why it guarantees O(n log n) performance.

Understand Selection Sort and Insertion Sort with intuitive analogies, traced examples, Java code, and a side-by-side comparison of when to use each.

Learn how Bubble Sort works with a detailed step-by-step walkthrough, Java implementation, and Big-O analysis. The easiest sorting algorithm to understand for beginners.

Learn what algorithms are, why they matter, and how Big-O notation helps us measure their efficiency. Includes easy-to-follow examples, Java code, and a complexity cheat sheet.

A complete, beginner-friendly guide to algorithms and data structures. Learn sorting, searching, trees, graphs, dynamic programming, and more — with Java examples.