- Introduction
- Chapter 1: Understanding the Importance of Big O Notation
- What is Big O Notation?
- Why is Big O Important?
- Practical Applications
- Optimization Strategies
- Chapter 2: The Limitations of Basic Data Structures
- Challenges with Arrays
- Challenges with HashMaps
- Challenges with LinkedList and DoublyLinkedList
- Chapter 3: Tree and Related Data Structures
- Binary Search Tree (BST)
- AVL Trees
- Red-Black Trees
- B-Trees
- Tries (Prefix Trees)
- Binary Heaps
- Summary of Tree Data Structures
- Chapter 4: Cloud Data Structures
- Bloom Filters
- HyperLogLog
- Count-Min Sketch
- t-digest
- SimHash
- Min-Hash
- Merkle Trees
- Chapter 5: Cache Eviction Strategies
- Least Recently Used (LRU)
- Least Frequently Used (LFU)
- Chapter 6: Hands-on Designing a File System Desktop Application
- Features
- File Structure
- Implementation
- Conclusion
- Appendices
- Appendix A: BinarySearchTree.ts
- Appendix B: AVLTree.ts
- Appendix C: RedBlackTree.ts
- Appendix D: Trie.ts
- Appendix E: BTree.ts
- Appendix F: MaxHeap.ts
- Appendix G: MinHeap.ts
- Appendix H: LFUCache.ts
- Appendix I: LRUCache.ts
- Appendix J: Probabilistic Data Structures
Advanced Data Structures Handbook: The JavaScript Edition
Simplifying Complexity for Real-World Applications
Designed for JavaScript developers, this handbook dives into the practical implementation of advanced data structures such as B-Trees, Tries, and probabilistic models like Bloom Filters. Focused on real-world challenges, it explains how to handle large datasets, optimize caching, and implement efficient searches. With clear examples and technical depth, this book offers a realistic approach to applying advanced concepts in scalable and reliable systems.
The author is letting you choose the price you pay for this book!
Designed for JavaScript developers, this handbook dives into the practical implementation of advanced data structures such as B-Trees, Tries, and probabilistic models like Bloom Filters. Focused on real-world challenges, it explains how to handle large datasets, optimize caching, and implement efficient searches. With clear examples and technical depth, this book offers a realistic approach to applying advanced concepts in scalable and reliable systems.
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"Advanced Data Structures Handbook: The JavaScript Edition" is a practical, accessible guide for JavaScript developers looking to master advanced data structures with real-world applications. Moving beyond basic arrays and hashmaps, this book introduces foundational concepts and provides step-by-step implementations of advanced structures such as B-Trees, Tries, and Red-Black Trees. It highlights their practical use in critical areas like file systems, caching, and database management.
Delving deeper, the book explores probabilistic data structures, including Bloom Filters and Count-Min Sketches, to demonstrate how these tools can efficiently manage large datasets with scalability in mind. Each chapter combines clear explanations with JavaScript-based code snippets and practical scenarios, empowering readers to understand the strengths of each structure and when to apply them—whether for prefix matching, optimizing memory usage, or approximate data analysis.
Whether you're an aspiring developer or a seasoned engineer tackling complex challenges, this handbook equips you with the knowledge and tools to enhance your problem-solving skills and make informed decisions when working with advanced data structures.
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Hela Ben Khalfallah
Hello! I’m Héla Ben Khalfallah, a senior software engineering with a focus on modern web solutions.
I’m a passionate software engineer crafting elegant and high-performing web experiences. I have a special love for React, Node.js, and Python, and thrive in full-stack development, seamlessly working across the frontend, backend, and related configurations. My transversal skillset enables me to adapt to diverse challenges, ensuring robust and well-rounded solutions.
I enjoy exploring software architecture and design (architecture styles, design patterns, clean code), FrontendOps (code generators, CLI tools, configurations), and advanced software concepts (optimal algorithms, data structures, Big O). My focus is on optimizing performance, streamlining workflows, and building websites that are not only visually stunning but also SAGES (Semantic, Accessible, Green, Easy, and Secure).
Beyond coding, I’m passionate about simplifying software engineering by breaking down complex problems into elegant solutions and clearly communicating technical concepts. I channel this enthusiasm through my blog, where I share insights, and through storytelling at conferences, meetups, and events.
Driven by a constant desire to learn and innovate, I’m always pushing the boundaries of my skills and embracing opportunities to explore new technologies.
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