Quick Sort is a highly efficient, comparison-based sorting algorithm that uses the divide-and-conquer strategy. It selects a pivot element, partitions the array into elements smaller than the pivot and elements larger than the pivot, then recursively sorts each partition. Its average-case time complexity is O(n log n), making it one of the fastest general-purpose sorting algorithms in practice.
Infix notation is the standard way we write arithmetic expressions, with operators between operands — e.g., A + B. Postfix notation (also called Reverse Polish Notation or RPN) places operators after their operands — e.g., A B +. Postfix expressions can be evaluated by machines without needing parentheses or operator-precedence rules, making them ideal for expression evaluators and compilers. In this post, we implement a Java program that converts an infix expression to its equivalent postfix form using a character stack and an operator-precedence table.
Graph traversal is the process of visiting all nodes in a graph in a systematic order. It is a fundamental operation in graph algorithms used for pathfinding, connectivity analysis, cycle detection, and more. There are two standard traversal strategies: Breadth-First Search (BFS) — Explores all neighbours of the current node before going deeper. Uses a queue internally. Depth-First Search (DFS) — Explores as far as possible along each branch before backtracking. Uses recursion (implicit call stack) internally. In this post, we implement both BFS and DFS on an undirected graph represented as an adjacency matrix.
Postfix notation (also called Reverse Polish Notation or RPN) places every operator after its operands. For example, the infix expression (6 - (2 + 3)) * (3 + 8/2) becomes the postfix expression 623+-382/+*. Evaluating postfix expressions is straightforward using a stack — no parentheses or precedence rules are needed. This post implements a postfix evaluator in Java using an integer stack. The program accepts a postfix string as input and prints the computed result.
Java's String class provides a rich set of built-in methods for manipulating text. In this post, we demonstrate the most commonly used string functions — including case conversion, length, concatenation, trimming, character access, equality checks, and index searching — through a simple interactive Java program.
A stack is a LIFO (Last In, First Out) data structure where elements are inserted and removed from the same end, called the top. While a stack is commonly implemented using a fixed-size array, it can also be backed by a linked list — which removes the size constraint entirely and allocates memory only as elements are pushed. In this post, we implement a stack using a singly linked list in Java. Each push operation adds a new node at the head of the list, and each pop removes the head node — making both operations O(1).
A circular queue is a fixed-size queue where the storage array is treated as a ring. When elements are dequeued from the front, those positions become available again for future insertions — eliminating the wasted space problem of linear array queues. The queue follows the FIFO (First In, First Out) principle: elements are added at the rear and removed from the front. This post presents a circular queue implementation in Java using a static array-backed design, demonstrating enqueue, dequeue, peek, and display operations through a menu-driven console program.
A Doubly Linked List (DLL) is a linked data structure where each node holds a value and two pointers: one pointing to the next node and one pointing to the previous node. This bidirectional linkage enables forward and reverse traversal — something a singly linked list cannot do without extra memory. A doubly-linked list: each node stores a value, a link to the next node, and a link to the previous node. In this post, we implement a DLL in Java that supports insertion at the first position, last position, after a given position, and before a given position — as well as deletion, search, and both forward and reverse display.
A Circular Queue (also called a Ring Buffer) is a queue data structure that treats its underlying array as if it were connected end-to-end in a circle. Unlike a linear queue, once the rear pointer reaches the end of the array, it wraps back to index 0 — allowing reuse of freed slots without shifting elements. This post implements a true circular queue in Java using an array, with proper wraparound logic for both the front and rear pointers. How a Circular Queue Works Both front and rear start at -1 (empty state). Enqueue: Advance rear with wraparound: rear = (rear + 1) % size. The queue is full when (rear + 1) % size == front. Dequeue: Advance front with wraparound: front = (front + 1) % size. Reset both to -1 when the last element is removed. Circular property: Elements can be added to index 0 again after front has moved past it.
A Binary Search Tree (BST) is a node-based binary tree data structure where each node stores a key, and every node in the left subtree holds a key strictly smaller than the parent, while every node in the right subtree holds a key strictly greater. This ordering property makes BSTs excellent for fast lookup, insertion, and deletion — all in O(log n) time on average. In this post, we implement a BST in Java that supports insertion, search, and three traversal orders: inorder, preorder, and postorder. BST Properties One node is designated the root of the tree. Each internal node contains a key and has at most two child subtrees. The left subtree of a node contains only keys strictly less than the node's key. The right subtree of a node contains only keys strictly greater than the node's key. Each subtree is itself a valid BST.