@ankurm

Ankur in Spring Cloud

Setting Up Eureka Server Using Spring Cloud (Part 1)

⚠️ This tutorial covers an old Spring Cloud version. Eureka itself is still actively maintained, but this setup targets Spring Boot 1.x/2.x. For Spring Boot 3.x, see the updated Service Discovery with Eureka guide and the Spring Cloud Netflix migration guide. This is a quick example for setting up Eureka server using Spring Cloud. You can download the whole project by using following link. Spring Cloud (V2.3.1) Eureka SeverDownload For this tutorial, we will be creating a New Maven Project. To keep thing more simple we will be creating a simple maven project i.e. we will be skipping archetype selection. New Maven Project Wizard - Creating a simple project

Ankur in Archived

Struts 2 Hello World Example (XML Version)

Security Warning: The dependency versions in this tutorial (struts2-core-2.2.1, ognl-3.0, javassist-3.7.ga, freemarker-2.3.16, commons-io-1.3.2, xwork-core-2.2.1) are from 2010–2011 and contain known critical vulnerabilities including remote code execution (RCE) exploits. Do not use these JARs in any production application. For current Struts 2, use the latest release from struts.apache.org and manage dependencies via Maven. This post is preserved for historical reference only. In this tutorial, we will be creating a simple “Hello world” program using Struts 2. For this tutorial we will be using Eclipse, Struts 2. Struts 2 allows you to define configuration either by using traditional Struts 1 like XML way or by using annotations. In this tutorial we will be following traditional XML way. Let’s move ahead!

Ankur in MSD

Implementing JPEG Algorithm in Java

The JPEG (Joint Photographic Experts Group) compression standard is the most widely used format for digital photographs on the web. Unlike lossless codecs, JPEG achieves very high compression ratios by discarding perceptually insignificant information from the image. At its core, the algorithm transforms pixel data into the frequency domain, aggressively quantises the high-frequency components (which the human eye is less sensitive to), and then encodes the result efficiently. This Java program demonstrates the key computational stages of JPEG compression applied to a single 8×8 pixel block: the Discrete Cosine Transform (DCT), quantisation, zigzag scan, and a simplified entropy encoding step. This example provides an educational look at the key stages of JPEG compression. JPEG Compression Pipeline A real JPEG encoder processes an image in the following sequence. This program implements all four stages for one 8×8 luminance block: Input block — An 8×8 grid of pixel intensity values. DCT — Converts spatial pixel data into frequency-domain coefficients. Quantisation — Divides each DCT coefficient by a value from the standard luminance quantisation table and rounds to the nearest integer, discarding fine detail. Zigzag scan — Reorders the 8×8 quantised coefficients into a 1D array, placing the most significant low-frequency coefficients first. Entropy encoding — Encodes the 1D array using a simplified run-length + binary scheme similar to the actual JPEG Huffman coding step.

Ankur in MSD

Implementing Run Length Encoding in Java

Run-Length Encoding (RLE) is one of the simplest lossless data compression techniques. Instead of storing every character individually, it replaces consecutive runs of the same character with a single instance of that character preceded by a count. For example, the string AAABBC becomes 3A2B1C. RLE works best on data with long repeated runs, such as bitmap images or binary sequences, and is often used as a preprocessing step in more sophisticated codecs like JPEG and fax compression standards. This Java program reads a string from the user, applies RLE compression using hexadecimal run-length counts, and reports the encoded output along with the original length, encoded length, and the resulting compression ratio.

Ankur in MSD

Animating a Truck in C

Computer graphics animation is the technique of creating the illusion of movement by rapidly drawing and erasing images on screen. In the Borland Turbo C environment, the graphics.h library provides low-level drawing functions that make it straightforward to build simple frame-by-frame animations. In this post, we walk through a C program that animates a truck moving across the screen using rectangles and circles to represent the truck body and wheels. What the Program Does The program draws a simple truck shape — a large rectangle for the cabin/body, a smaller rectangle for the cab, and two circles for the wheels — then shifts this shape incrementally across the screen to create an animation effect. Between each frame the viewport is cleared, giving the impression of smooth movement.

Ankur in DC

Demonstrating Bully Algorithm in Java

The Bully Algorithm is a classic election algorithm used in distributed systems to elect a coordinator (leader) among a group of processes. When a process notices that the current coordinator is no longer responding, it initiates an election. The process with the highest priority among all active (running) processes wins the election and becomes the new coordinator. This Java program simulates the Bully Algorithm with user-defined processes, each having a status (active or inactive) and a priority value.

Ankur in DC

Demonstrating Deadlock with Resource Allocation

Deadlock is a situation in a distributed or multi-process system where a set of processes are permanently blocked, each waiting for a resource that another process in the set holds. Detecting which processes are causing a deadlock is a critical operating system responsibility. This C program implements a deadlock detection algorithm using a resource allocation graph. It uses a claim matrix (maximum resource needs), an allocation matrix (currently held resources), and availability vectors to identify processes that are involved in a deadlock.

Ankur in Snippets

Demonstrating Transposition Cipher in Java

A transposition cipher is a method of encryption where the positions of characters are shifted according to a certain system, without changing the actual characters themselves. It rearranges the characters in a message to create ciphertext, and the same method in reverse restores the original message. This post walks you through how a transposition cipher works using a Java program. This particular example arranges characters into a matrix and reads them column-wise (for encryption) or row-wise (for decryption). How the Transposition Cipher Works Encryption: Fill a matrix column-wise with characters of the message. Read the characters row-wise to get the encrypted message. The operation is repeated twice for added confusion. Decryption: Reverse the above process by filling the matrix row-wise. Read it column-wise to retrieve the original message.

Ankur in Snippets

C++ Implementation of Substitution Cipher

This simple C++ implementation of a substitution cipher—specifically the Caesar cipher—demonstrates how basic cryptographic techniques can be used with file handling. The Caesar cipher is one of the oldest and simplest substitution cipher techniques. It works by shifting the letters in a message by a fixed number of positions in the alphabet. Unlike transposition ciphers, which rearrange character positions, substitution ciphers replace characters with others based on a defined scheme. This blog post demonstrates a C++ implementation that reads a message from a file, performs Caesar cipher encryption or decryption, and writes the result to another file. How It Works Input and Output Files: Input is read from a file named anip.txt. Output is written to a file named anop.txt. User Choices: You can choose between encryption and decryption. Provide a key (shift amount), e.g., 2. Caesar Cipher Logic: For encryption, each letter is shifted forward in the alphabet by the key. For decryption, each letter is shifted backward by the key. Non-alphabet characters are left unchanged.

Ankur in Snippets

Java Program to Demonstrating RSA

In the world of cryptography, RSA (Rivest–Shamir–Adleman) is a popular public-key cryptosystem widely used for secure data transmission. It’s based on the principle that while multiplying large prime numbers is computationally easy, factoring their product is not — which ensures security. This post will walk you through how RSA encryption and decryption work using a simple Java program. You'll learn how the sender encrypts a message using the recipient’s public key, and how the receiver decrypts it using their private key. What Happens Under the Hood? The RSA algorithm follows these steps: Key Generation Choose two large prime numbers p and q. Compute N = p * q. Compute the totient function: phi = (p-1)(q-1). Choose an integer e such that 1 < e < phi and gcd(e, phi) = 1. Compute d, the modular inverse of e modulo phi. Encryption The sender uses the recipient’s public key (e, N) to compute ciphertext: c = m^e mod N. Decryption The recipient uses their private key (d, N) to decrypt: m = c^d mod N.