"Data Structures & Algorithms using Kotlin" is considered one of the most practical books for anyone who wants to master fundamental data structures and algorithms using the modern Kotlin language. The author, Hemant Jain, organizes the material from basic algorithm analysis to advanced techniques in dynamic programming and complexity theory. Unlike textbooks that deliver dry theory, this guide combines explanations, code examples, and exercises, making it a valuable resource for both students and professional developers.
Each topic is reinforced with hands-on exercises and walkthroughs, helping readers build problem-solving skills in settings close to interviews and real-world projects. The book is used by practitioners to prepare for interviews and as a desk reference in day-to-day work.
Who is this book for?
It’s intended for readers who aren’t just learning Kotlin but aim to deeply understand computer science fundamentals.
- Computer science students - receive a systematic introduction to algorithms and data structures with practical Kotlin code.
- Developers preparing for interviews - can practice classic problems commonly found in top tech-company screenings.
- Programmers transitioning to Kotlin - will find implementations of familiar algorithms and structures in the Kotlin paradigm.
- Hands-on engineers - can use the ready-made implementations as a foundation for production code.
How is this book different from other Kotlin resources?
Most algorithm books are based on C++, Java, or Python, while Kotlin is rarely used in this domain. "Data Structures & Algorithms using Kotlin" fills that gap by providing a systematic guide tailored to a language widely used in Android and server-side development.
The author goes beyond basic definitions. Every chapter includes complexity analysis, practical code examples, and exercises for reinforcement. This theory-plus-practice approach is considered the most effective way to learn.
A major strength is the structure: it covers all key areas - arrays, lists, stacks, queues, trees, hash tables, graphs, search and sort algorithms, and optimization methods (dynamic programming, greedy algorithms, backtracking). Additional chapters on complexity theory and algorithm design make it a complete course.
Special attention is paid to comparing algorithms and choosing the optimal solution for each task - useful both for interview prep and real application design. The book also integrates examples with the author’s GitHub repositories, boosting trust: you can download and test production-proven code.
In short, the book stands out not only by language choice but by a comprehensive approach: from fundamentals to advanced techniques, with a focus on real problems and interview scenarios.
How do you apply this knowledge in practice?
- Implementing efficient data structures in Android applications.
- Optimizing search and sort routines in production projects.
- Designing graph algorithms (e.g., routing or relationship analysis).
- Using dynamic programming to solve optimization problems.
- Preparing for technical interviews and participating in programming contests.
The Developer's Opinion About the Book
As a developer working with Kotlin in real projects, I find this book extremely useful. Before it, I often had to pull examples from Java or C++ literature and then adapt them, which took time and introduced mistakes. Here, everything is structured specifically for Kotlin, saving effort and making learning highly practical.
A standout strength is the focus on complexity analysis. The author doesn’t stop at implementations - he shows how to choose the optimal algorithm for a given problem. That matters not only for interviews but also for production code, where runtime directly impacts performance and scalability.
The one drawback is that it’s not ideal for absolute beginners: without Kotlin basics and core CS concepts, the material can feel demanding. But for developers with some experience who want to systematize their knowledge of algorithms, this is one of the best resources available. It’s become my desk reference - I return to it when designing complex solutions and use it as a refresher while preparing for technical interviews.
Jason Nguyen, Data Scientist
FAQ for "Data Structures & Algorithms using Kotlin"
1. What does "Data Structures & Algorithms using Kotlin" offer, and how does it differ from other books?
It’s a systematic guide to classic data structures and algorithms written in Kotlin. Unlike Java- or C++-centric textbooks, it emphasizes idiomatic Kotlin: collections, extensions, and functional style. The book covers not only basic structures (stack, queue, list, tree) but also advanced sorting, searching, and dynamic programming. Its key difference is that the material is adapted to a modern language rather than “translated” from Java.
2. What reader level will benefit the most?
It’s aimed at students and developers who know Kotlin basics and want a deeper grasp of algorithms. Beginners will find clear explanations and simple examples; mid-level developers can strengthen fundamentals and prep for interviews; experienced engineers can use it as a reference. It’s universal, but especially valuable for those mastering Kotlin as a tool for algorithmic problem solving.
3. Is the book suitable for interview preparation?
Yes. Data structures and algorithms are standard interview topics. "Data Structures & Algorithms using Kotlin" covers problems frequently seen in screenings: trees, graphs, and dynamic programming. The author provides code samples you can adapt and use for practice, making it a solid companion for interview prep.
4. Is there more theory or practice?
The balance leans toward practice. Each algorithm is presented step-by-step: idea → pseudocode → Kotlin implementation. Theory serves as a concise introduction, while the main focus is on how the algorithm works in code. This makes the book a working tool, not just a textbook.
5. Where are the book’s concepts applicable in real life?
Everywhere from mobile to server systems. In Android development, you need to handle collections efficiently and optimize memory; in backend systems, you’ll build performant search trees and leverage graph algorithms. The book helps establish a foundation needed in any domain involving data processing.
Information
| Author: | Hemant Jain | Language: | English |
| Publisher: | Hemant Jain | ISBN-13: | 978-9357803458 |
| Publication Date: | December 18, 2022 | ISBN-10: | 9357803459 |
| Print Length: | 572 pages | Category: | Data Science Books |
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