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    Ultimate Android Design Patterns: Master Android Design Patterns with Real-World Projects for Scalable, Secure

    Posted By: naag
    Ultimate Android Design Patterns: Master Android Design Patterns with Real-World Projects for Scalable, Secure

    Ultimate Android Design Patterns: Master Android Design Patterns with Real-World Projects for Scalable, Secure, and High-Performance Apps (English Edition)
    English | 2025 | ISBN: 9789348107459 | Pages: 827 | EPUB (True) | 48.57 MB

    Unlocking the Power of Design Patterns to Build Awesome Android Apps
    Key Features
    ● Learn creational, structural, behavioral, and architectural patterns to build scalable, maintainable, and testable apps.
    ● Apply design patterns in hands-on projects, including an e-commerce app, a social media platform, and a chat system.
    ● Enhance app efficiency with concurrency patterns, network security best practices, and performance optimization techniques.
    Book Description
    Design patterns are the backbone of well-structured software, enabling developers to write clean, reusable, and testable code. By mastering these patterns, you’ll enhance code efficiency, reduce technical debt, and future-proof your apps against rapid industry changes. 
    Ultimate Android Design Patterns
     is your essential guide to building scalable, maintainable, and high-performance Android applications.
    You’ll start with the fundamentals of design patterns, advance through architectural decisions and performance optimizations, and conclude with real-world project implementations. This book systematically explores creational, structural, behavioral, and architectural design patterns, demonstrating how they solve real-world coding challenges. You’ll implement these concepts through three hands-on projects—an e-commerce app, a social media platform, and a chat system—leveraging Kotlin, Jetpack Compose, Room, and Dependency Injection to create production-ready applications.
    Whether you’re an aspiring Android developer refining your fundamentals or an experienced programmer looking to elevate your app architecture, this book provides a structured learning path. Don't miss the opportunity to master the best practices that top Android engineers rely on—stay ahead in the fast-evolving world of mobile development!
    What you will learn
    ● Master design patterns to build scalable and maintainable Android apps
    ● Apply MVVM and MVI to create clean and modular app architectures
    ● Enhance code reusability with creational, structural, and behavioral patterns
    ● Develop real-world apps using Kotlin, Jetpack Compose, and Room Database
    ● Boost app performance by optimizing memory usage and CPU efficiency
    ● Improve testability with JUnit, Espresso, and Dependency Injection
    Table of Contents
    1. Overview of Design Patterns
    2. Design Patterns in Android Development
    3. Creational Patterns
    4. Structural Patterns
    5. Behavioral Patterns
    6. Architectural Patterns
    7. Concurrency, Network, and, Security Patterns
    8. Combining Patterns
    9. Performance Considerations
    10. Testing with Design Patterns
    11. Refactoring with Design Patterns
    12. Building an E-Commerce App
    13. Building a Social Media App
    14. Building a Chat App
    15. The Future of Android Development
           
    Index
    About the Authors
    Lorenzo Vainigli
     is an Italian Android engineer, born in 1994, with a deep passion for computer science and mobile technologies. His curiosity has led him to explore various fields, including artificial intelligence, open-source software, and the latest trends in Android development.
    After obtaining a diploma in accounting from the Istituto Bandini in Siena, where he was introduced to the basics of programming. He continued his studies at the University of Bologna. There, he earned a bachelor's degree in Computer Science in 2017, presenting a thesis on an Android application for managing personal financial flows. Later, in 2021, he obtained a master's degree in Computer Science with a thesis on the use of deep convolutional neural networks for diagnosing COVID-19 through voice recordings.