In this chapter, you'll develop essential skills in software efficiency analysis. You will learn to evaluate time and space complexity and compare the performance of sets, maps, and lists. By the end, you'll have the analytical foundation to assess software performance and select appropriate data structures for your Java applications.

Big-O notation: time complexity

Implementing a contacts management application

Time complexity in contact management

Implementing a sort checker application

Big-O notation: space complexity

Finding the max value in an array

Space complexity in find max value

Implementing a social network

Efficient data structures: Sets & Maps

Implementing a duplicate transaction finder

Implementing a text analysis application

Fundamentals of Software Performance

This chapter equips you with essential techniques for measuring Java application performance. You'll learn to identify bottlenecks using System.nanoTime(), understand JVM memory architecture, track memory and CPU usage, and explore how garbage collection and JIT compilation affect your code's efficiency. These skills will help you systematically diagnose and solve performance issues in your applications.

Understanding performance bottlenecks

Measuring operation time

Comparing search algorithm performance

Understanding JVM Memory Architecture

Identifying memory location

Implementing memory-efficient string processing

Performance metrics and measurement

Tracking memory usage

Analyzing CPU time

Garbage collection & Just-In-Time (JIT) compilation

Understanding Just-In-Time (JIT)

Optimizing a financial analysis application

Measuring Code Performance

This chapter introduces you to advanced techniques for optimizing Java application performance. You'll learn how to leverage multi-threading with both Thread objects and parallel streams to process operations concurrently. You'll explore thread pools with ExecutorService and asynchronous programming with CompletableFuture. The chapter also covers essential performance patterns including caching strategies to avoid redundant computations and efficient initialization techniques like the Singleton pattern. By implementing these approaches, you'll be able to significantly enhance your application's responsiveness and throughput.

Basic multi-threading principles

Creating parallel threads for processing

Optimizing image processing with parallel streams

Advanced threading patterns

Implementing a thread pool for batch processing

Implementing an asynchronous data processing pipeline

Caching strategies

Selecting an appropriate cache eviction policy

Implementing an LRU cache

Lazy initialization and singleton patterns

Implementing lazy initialization

Implementing the Singleton pattern

Wrap-up

Improving Code Performance

This course equips Java developers with essential skills to analyze and optimize performance in enterprise applications. You'll learn to evaluate algorithmic complexity with Big-O notation, choose efficient data structures, and monitor key metrics like CPU, memory, and latency using professional tools. By exploring Java Virtual Machine internals, garbage collection, and Just-In-Time compilation, you'll gain insights into runtime behavior. The course also covers advanced techniques such as multi-threading, asynchronous operations, and caching strategies, enabling you to build scalable, high-performance Java systems.

<h2>Understanding Code Performance Fundamentals</h2><p>Performance optimization is a critical skill for Java developers building enterprise-scale applications. This course provides a comprehensive foundation in code optimization techniques, from algorithmic complexity analysis to advanced performance patterns. You'll learn systematic approaches to identify, measure, and optimize performance bottlenecks in Java applications.</p><br><h2>Advanced Performance Analysis</h2><p>Begin with a deep dive into algorithmic complexity using Big-O notation. Through practical implementations with Java collections, you'll learn to evaluate both time and space complexity trade-offs. You'll master the selection of appropriate data structures based on performance requirements, understanding the implications of choosing between Lists, Sets, and Maps in different scenarios.</p><br><h2>JVM Performance Optimization</h2><p>Develop expertise in Java Virtual Machine internals and performance measurement. Learn to utilize professional tools to monitor crucial metrics including CPU utilization, memory consumption, and latency. You'll gain practical experience with garbage collection mechanisms and Just-In-Time compilation, enabling you to design applications that leverage the JVM's optimization capabilities effectively.</p><br><h2>Enterprise-Scale Performance Patterns</h2><p>Explore advanced optimization techniques essential for high-performance applications. Master concurrent programming with multi-threading and asynchronous operations, implement efficient caching strategies, and utilize initialization patterns that enhance application performance. Through practical examples, you'll learn to apply these patterns in real-world scenarios.<br>Upon completion, you'll possess the technical expertise to analyze application performance, implement optimization strategies, and design high-performance Java applications. This course equips you with the skills needed to address performance challenges in enterprise environments and build scalable, efficient systems.</p>

Input/Output and Streams in Java

Learn key techniques to optimize Java performance, from algorithm efficiency to JVM tuning and multithreading.

Optimizing Code in Java

Lead Engineer @Wealthyhood

Garbage collection - the basics

How garbage collection works

Garbage collection and performance

GC performance impact

GC-friendly coding

Just-In-Time compilation

JIT-friendly code patterns

Summary

Let's practice!

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Measuring Code Performance - Garbage collection & Just-In-Time (JIT) compilation

Garbage collection & Just-In-Time (JIT) compilation

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