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Preface: Why Data-Oriented Programming with Rust?
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Part I: Foundations
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Chapter 1: Introduction to Data-Oriented Programming
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Chapter 2: Rust Fundamentals for Data-Oriented Development
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Chapter 3: Memory Layout and Representation
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Part II: Core Data-Oriented Programming Principles
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Chapter 4: Separating Code from Data
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Chapter 5: Representing Data with Generic Structures
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Chapter 6: Immutability and Persistent Data Structures
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Chapter 7: Schema Validation and Type Safety
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Part III: Data-Oriented Design Patterns
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Chapter 8: Structure of Arrays (SoA) vs. Array of Structures (AoS)
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Chapter 9: Entity-Component-System (ECS) Architecture
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Chapter 10: Hot and Cold Data Splitting
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Chapter 11: Data Transformation Pipelines
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Part IV: Concurrency and Parallelism
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Chapter 12: Fearless Concurrency with Rust
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Chapter 13: Data Parallelism Patterns
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Chapter 14: Asynchronous Data Processing
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Part V: Memory Management and Optimization
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Chapter 15: Custom Allocators and Memory Pools
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Chapter 16: Zero-Copy and Minimizing Allocations
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Chapter 17: Unsafe Rust for Performance-Critical Code
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Part VI: Scalability and Distributed Systems
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Chapter 18: Designing for Horizontal Scalability
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Chapter 19: Serialization and Data Exchange
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Chapter 20: Data Storage and Persistence
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Part VII: Real-World Applications
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Chapter 21: Building a High-Performance Data Processing Engine
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Chapter 22: Implementing a Game Engine with ECS
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Chapter 23: Network Protocol Implementation
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Chapter 24: Data Analytics and Stream Processing
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Part VIII: Advanced Topics and Best Practices
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Chapter 25: Profiling and Performance Analysis
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Chapter 26: Testing Data-Oriented Systems
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Chapter 27: API Design for Data-Oriented Libraries
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Chapter 28: Evolving and Maintaining Data-Oriented Codebases
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Part IX: The Future of Data-Oriented Programming
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Chapter 29: Emerging Patterns and Techniques
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Appendices
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Appendix A: Rust Setup and Development Environment
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Appendix B: Performance Optimization Checklist
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Appendix C: Glossary of Terms
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Appendix D: Further Reading and Resources
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Closing Credits
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