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AlgoEmbedded
Data Structures and Algorithms for Embedded Systems
This book is 100% completeLast updated on 2026-02-09
Stop writing code that only works on your laptop.
Your O(n²) sorting algorithm runs fine on an i9 processor. But on a Cortex-M4 with 2KB of RAM? It crashes the stack.
AlgoEmbedded is the first textbook that stops teaching "Computer Science" and starts teaching Embedded Engineering. Learn how to adapt standard algorithms for the constraints of the real world.
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About
About the Book
AlgoEmbedded: Data Structures and Algorithms for Embedded Systems bridges the gap between abstract Computer Science theory and the harsh reality of embedded hardware.
While traditional textbooks teach you how to write algorithms in Python or Java with unlimited memory, AlgoEmbedded prepares you for the world of Kilobytes and Microseconds. This book doesn't just show you how to implement a Linked List or a PID Controller; it teaches you why certain algorithms fail on a microcontroller and how to design robust, resource-efficient solutions.
What You Will Learn:
- Constraint-Aware Coding: Implement dynamic data structures (Heaps, Trees, Graphs) without dynamic memory allocation (malloc).
- Real-Time Algorithms: Master scheduling (RMS/EDF) and control loops (PID, Kalman Filters) that meet strict deadlines.
- Modern Embedded Trends: Explore Edge AI (TinyML), IoT Security, and Power Optimization techniques.
- Practical Engineering: Move beyond LeetCode puzzles to solve real-world problems like sensor noise filtering, task scheduling, and robot navigation.
Written by Dr. Tri-Vien Vu, Head of the Automation and Control Engineering Department at Ton Duc Thang University, this book is the missing manual for Electrical and Electronics students who want to become professional Firmware Engineers.
Stop writing code that works on your laptop. Start writing code that works in the real world.
Author
About the Author
Tri-Vien Vu
Lecturer and Head of Automation and Control Engineering, focusing on embedded systems, robotics, and system-level engineering education. Interested in applying AI as a tool for teaching and control system design, with emphasis on safety, real-time behavior, and engineering responsibility
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