1. JVM Internals and Performance Tuning
   Understanding the Java Virtual Machine (JVM) internals is fundamental for advanced developers to optimize performance and troubleshoot issues.

a. Class Loading Mechanism
Java's class-loading mechanism follows a hierarchical, lazy loading approach. Classes are loaded into memory only when they are first referenced, using class loaders like Bootstrap ClassLoader, Extension ClassLoader, and Application ClassLoader.

Understanding class loading is important for advanced tasks like managing classpath issues, dynamically loading classes, and working with frameworks that heavily rely on class loading (eg, Spring).

b. JVM Memory Management
Memory in JVM is divided into different sections like the heap, stack, metaspace, and young/old generations. Knowing how memory allocation, garbage collection, and memory leaks work is key to optimizing application performance.

Garbage Collection (GC): Advanced developers must be familiar with various garbage collectors like G1GC, CMS, and ZGC, and how to tune them based on application requirements.
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java -Xms512m -Xmx1024m -XX:+UseG1GC -XX:MaxGCPauseMillis =200 MyApp
c. Just-In-Time (JIT) Compilation
JIT compiles bytecode into native machine code for performance optimization. Understanding how JIT works can help in diagnosing performance bottlenecks and interpreting JIT-related flags in profiling tools.

1. Concurrency and Multithreading
   Concurrency in Java allows you to perform multiple tasks simultaneously, leveraging multi-core processors for better performance.

a. Java Concurrency API
Advanced Java developers must be familiar with the Concurrency API introduced in Java 5, including classes from the java.util.concurrent package like:

ExecutorService: For managing thread pools.
CountDownLatch and CyclicBarrier: For synchronizing multiple threads.
ForkJoinPool: For parallel task execution in divide-and-conquer algorithms.
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ExecutorService executor = Executors.newFixedThreadPool(4);
executor.submit(() -> performTask());
b. Thread Safety and Synchronization
Thread safety ensures that shared resources are not corrupted by concurrent threads. Synchronization techniques include:

Synchronized blocks: Ensures that only one thread can access a critical section at a time.
ReentrantLock: Provides more control than synchronized blocks with features like fair locking and timed waits.
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synchronized(lock) {
// Critical section
}
c. Atomic Classes and Lock-Free Programming
Java provides atomic classes (AtomicInteger, AtomicReference, etc.) for lock-free thread-safe operations. Lock-free programming is crucial for minimizing contention in highly concurrent systems. Java classes in Pune

1. Memory Models and Performance
   The Java Memory Model (JMM) defines how threads interact with memory and the visibility of shared variables.

a. Happens-Before Relationship
Understanding the happens-before relationship is key to reasoning about the correctness of concurrent programs. The JMM guarantees that certain actions (like releasing a lock) happen-before others (like acquiring the same lock), ensuring memory consistency.

b. Volatile Keyword
The volatile keyword ensures that the value of a variable is always read from main memory, rather than from a thread's local cache. This is crucial for scenarios where multiple threads are reading and writing to shared variables.

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private volatile boolean running = true;
4. Design Patterns
Design patterns offer well-established solutions to common design problems. Advanced developers must be proficient in recognizing and applying them in real-world scenarios.

a. Creational Patterns
Singleton: Ensures that a class has only one instance, with a global point of access.
Factory Method: Defines an interface for creating objects but lets subclasses alter the type of objects that will be created.
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public class Singleton {
private static Singleton instance = null;

private Singleton() {}

public static synchronized Singleton getInstance() {
    if (instance == null) {
        instance = new Singleton();
    }
    return instance;
}

}
b. Structural Patterns
Decorator: Allows behavior to be added to individual objects dynamically without affecting others.
Proxy: Controls access to another object, especially useful for lazy loading, security, and logging.
c. Behavioral Patterns
Observer: Defines a one-to-many dependency, where changes in one object trigger updates to other objects.
Strategy: Allows an algorithm's behavior to be selected at runtime.
5. Advanced Functional Programming
With the introduction of lambda expressions and the Streams API in Java 8, functional programming paradigms have become an essential skill for Java developers.

a. Lambda Expressions
Lambdas allow you to write concise code by passing behavior as a parameter. They are often used with collections and streams to replace verbose anonymous inner classes.

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List names = Arrays.asList("John", "Jane", "Doe");
names.forEach(name -> System.out.println(name));
b. Streams API
The Streams API simplifies collection processing by allowing developers to chain operations like map, filter, and reduce.

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List numbers = Arrays.asList(1, 2, 3, 4, 5);
int sum = numbers.stream().filter(n -> n % 2 == 0).mapToInt(Integer::intValue).sum();
c. Functional Interfaces and Method References
Functional interfaces (e.g., Runnable, Supplier, Function) allow you to treat methods as first-class citizens. Method references (Class::method) provide even more concise syntax for lambdas.

1. Java Streams and Parallelism
   Parallel streams enable multi-core processing, making it easier to divide workloads across threads. However, parallelism introduces challenges in data consistency and race conditions.

a. Parallel Streams
Parallel streams split a collection into chunks and process them concurrently, providing better performance in CPU-bound operations.

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List list = Arrays.asList("a", "b", "c");
list.parallelStream().forEach(System.out::println);
b. Avoiding Race Conditions
When using parallel streams or multi-threading, be cautious about mutable shared state, which can lead to race conditions. Always ensure shared resources are thread-safe, either by using thread-safe collections (ConcurrentHashMap) or avoiding shared state.

1. Building Scalable and Resilient Systems
   Scalability and resilience are crucial when developing large-scale Java applications, especially in cloud environments.

a. Microservices Architecture
Java is commonly used in microservices architectures due to its robust frameworks like Spring Boot. Understanding how to design microservices with loose coupling, fault tolerance, and scalability is key.

b. Reactive Programming
Reactive programming in Java (using frameworks like RxJava and Project Reactor) allows for handling asynchronous streams of data efficiently, particularly in environments that require responsiveness and low-latency.

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Flux flux = Flux.just(1, 2, 3).map(i -> i * i);
c. Circuit Breakers and Fault Tolerance
In distributed systems, circuit breakers (eg, using Hystrix or Resilience4j) prevent cascading failures by monitoring services and halting requests when the system is under stress.

1. Advanced Testing and Continuous Integration
   Writing tests for complex systems ensures code quality and stability, but advanced testing techniques are needed for larger codebases.

a. Unit and Integration Testing
Tools like JUnit and TestNG are essential for unit testing, but advanced developers must also master integration testing and testing asynchronous code.

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@Test
public void testService() {
assertEquals(expected, actual);
}
b. Test Containers
Using TestContainers allows you to run actual databases or services in lightweight Docker containers during integration testing.