Data Structures and Algorithms in JavaScript - Federico Kereki

This book addresses one of the most glaring gaps in JavaScript developers' knowledge base--basic computer science concepts, like data structures and algorithms, for solving complex problems. For JavaScript developers, this book is a one-stop-shop for learning the algorithms and data structures that solve and optimize complex problems--covering everything from functional programming and abstract data types, to sorting and searching, lists, bags, binary trees, forests, heaps, and graphs. The author's use of examples taken from coding challenges and programming interviews enables you to explore the real-world advantages of specific algorithms and data structures. Written and illustrated to be a developer's go-to reference manual for immediate on-the-job applications, performance--both from a theoretical point of view and a practical standpoint--is emphasized alongside every algorithm or data structure introduced. In addition to demonstrating best practices throughout the text, each chapter ends with a series of questions and examples that clarify the preceding concepts. The book utilizes the latest version of JavaScript (ECMAScript) and its more modern features wherever appropriate. \nNot the Same Old JavaScript. Think you know JavaScript? Think again. This isn't your typical coding book--it's a deep dive into the powerful world of data structures and algorithms that will transform the way you approach problem solving in JavaScript. Whether you're a frontend developer tackling complex applications, a backend engineer building scalable systems, or a programmer preparing for technical interviews, this book will revolutionize the way you code. Key features include: \n Modern JavaScript techniques: Use the latest language features and functional programming principles for cleaner, more efficient code. Performance-focused approach: Analyze and optimize algorithms using Big O notation. Essential algorithms explained: Implement and fine-tune core algorithms like quicksort, merge sort, digital search, and binary search. Algorithm design strategies: Solve challenging problems with techniques like recursion, dynamic programming, backtracking, and brute-force search. Advanced data structures: Explore complex structures such as binary search trees, heaps, and graphs. \nEach chapter is carefully crafted with clear, no-nonsense explanations of complex concepts, real-world coding examples, and challenging questions (with answers at the end) to reinforce your understand