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Reference Counting vs Tracing: Types of Garbage Collection

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 Memory management is a crucial aspect of software development. While developers often write the code that creates and uses data structures, the actual cleanup of unused memory is typically handled behind the scenes by garbage collection mechanisms . Two of the most common types of garbage collection techniques are Reference Counting and Tracing . In this post, we’ll explore how these two techniques work, compare their strengths and weaknesses, and explain how they relate to Garbage Collection in Data Structure implementations across various programming languages. What Is Garbage Collection? Before diving into the types, it’s important to understand what garbage collection is: the process of automatically identifying and reclaiming memory that is no longer in use by a program. Without garbage collection, developers would have to manually free memory—an error-prone and difficult task that can lead to memory leaks or dangling pointers . Garbage collection solves this by auto...
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How Java Handles Addition with Different Numeric Data Types

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 When working with arithmetic in Java, especially the addition of two numbers in Java , it's important to understand how the language handles different numeric data types. Java is statically typed and enforces strict type conversion rules, which can lead to unexpected results or even compilation errors if you're not careful. In this post, we’ll explore how Java performs addition across various primitive numeric types such as byte , short , int , long , float , and double . Java's Numeric Data Types: A Quick Overview Java provides several primitive numeric data types: Type Size Range byte 8-bit -128 to 127 short 16-bit -32,768 to 32,767 int 32-bit -2^31 to 2^31-1 long 64-bit -2^63 to 2^63-1 float 32-bit Approximately ±3.40282347E+38F double 64-bit Approximately ±1.79769313486231570E+308 Addition Between Same Data Types Example: int + int int a = 10 ; int b = 20 ; int result = a + b; System.out.println(result); // Output: 30 This is straightforward. The ty...
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Using Arrays to Store Fibonacci Numbers in Java

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  The Fibonacci Series is a classic sequence where each number is the sum of the two preceding ones. In Java, one efficient way to generate and store the Fibonacci numbers is by using arrays. This approach helps when you want to access any Fibonacci number multiple times without recalculating it. In this blog, we’ll discuss how to implement a Fibonacci Series program in Java using arrays. What Is the Fibonacci Series? The Fibonacci sequence starts like this: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, ... Every number is calculated as: F(n) = F(n-1) + F(n-2) Why Use Arrays? Using arrays to store Fibonacci numbers allows you to: Store all the computed numbers in memory for quick access. Avoid redundant calculations, especially useful for larger sequences. Easily print or manipulate the entire sequence later. Java Program to Store Fibonacci Numbers in an Array public class FibonacciWithArray { public static void main (String[] args) { int n = 10 ;...
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How Schedules Affect Database Consistency in Real-World Applications

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 In the world of database management systems (DBMS), consistency is a cornerstone of data integrity and reliability. Behind the scenes, a well-structured schedule in DBMS plays a vital role in maintaining this consistency, especially in multi-user and high-concurrency environments. But what exactly are schedules, and how do they influence the consistency of your database in real-world applications? Let’s break it down. What Is a Schedule in DBMS? A schedule in DBMS refers to the order in which multiple database transactions are executed. When several transactions run concurrently, their operations—such as reading, writing, or committing—can interleave. This interleaving forms a schedule, and the correctness of that schedule determines whether the database stays consistent. Why Is Consistency So Important? Consistency ensures that a database transitions from one valid state to another after a transaction completes. If a schedule in DBMS violates consistency rules, it can ...
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React 19: What’s New and How It Impacts Full Stack Development

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 React continues to shape the modern JavaScript ecosystem, and with the release of React 19 , developers can expect significant advancements that influence both frontend and backend development. Whether you're an experienced developer or just starting your full stack journey, understanding React 19 is essential for building faster, more scalable, and more maintainable applications. At TechnoGeeks Training Institute , we ensure our training programs stay aligned with the latest technologies. This article explores the key features of React 19 and how they impact full stack development. What’s New in React 19? 1. React Server Components (RSC) – Officially Stable One of the most anticipated features, React Server Components, is now stable in React 19. RSC allows developers to offload component rendering to the server, reducing the amount of JavaScript sent to the browser and improving page load performance. Impact on Full Stack Development: Improved server-side rendering integra...
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Garbage Collection in JVM: How It Affects Data Structures

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  Memory management is one of the most crucial aspects of software development — and in Java, it's largely handled by the Java Virtual Machine (JVM) through Garbage Collection (GC) in Data Structure . While this automatic memory handling simplifies programming, it also has direct implications for how data structures are stored, accessed, and discarded. In this blog, we'll explore how garbage collection in the JVM works and how it impacts the performance and behavior of commonly used data structures. What Is Garbage Collection in JVM? Garbage Collection is the process by which the JVM automatically removes objects that are no longer reachable in the application. This reclaims heap memory, preventing memory leaks and out-of-memory errors without requiring manual deallocation. The JVM uses various garbage collection algorithms, including: Serial GC Parallel GC CMS (Concurrent Mark-Sweep) G1 GC (Garbage First) ZGC and Shenandoah (for ultra-low pause application...
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Nested Virtualization in the Cloud: Running Virtual Machines Inside VMs

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 Cloud computing has changed the way businesses build, deploy, and scale infrastructure. As virtualization technologies continue to evolve, one advanced concept is gaining traction: nested virtualization . This technique allows you to run a virtual machine inside another virtual machine , unlocking powerful use cases for development, testing, and hybrid environments. In this post, we’ll explore what nested virtualization is, how it works in the cloud, and why it’s becoming increasingly important in the era of CPU Virtualization in Cloud Computing . What Is Nested Virtualization? Nested virtualization refers to the ability to run a hypervisor (a virtual machine manager) inside a virtual machine , allowing that VM to host its own virtual machines. Put simply: Traditional virtualization = physical server → virtual machines Nested virtualization = physical server → VM → another layer of VMs inside This is made possible by modern CPU features (like Intel VT-x and AMD-V) an...
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