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Packed with production-grade code, this hands-on textbook/guide empowers readers to build, secure, and optimize software at the system boundary.
Mastering low-level Linux/Unix environments requires bridging the gap between user-space interfaces, kernel mechanisms, and distributed network architectures. Grounded in hands-on, production-grade code, this comprehensive guide takes readers on a complete journey through command-line shell environments, process, memory and file management, and robust concurrent server design.It addresses the full stack of Linux/Unix systems engineering, from shell interfaces to low-level kernel routines and high-performance network architectures.
Topics and features:
·Unifying architecture: seamlessly integrates command-line tool use, core system calls, and network mechanics into a single, cohesive progression
·Hands-on mastery: includes end-of-chapter review questions, structured lab exercises, and capstone projects to reinforce low-level problem solving
·Theory to implementation: pairs essential OS principles-such as synchronization, process scheduling, and memory mapping-directly with practical Unix execution
·Production-ready code: features over 400 practical C, Python, Java and shell snippets designed for immediate application and deep technical analysis
·Mini-kernel blueprint: delivers a step-by-step walkthrough to design and implement a functional mini kernel from the ground up
This comprehensive volume serves as a primary textbook and desktop reference for upper-level computer science students, university instructors, and system programming researchers. Additionally, it can serve as an invaluable guidebook for software developers, cybersecurity professionals, system administrators, and operating system developers working on Linux/Unix platforms who seek practical, example-driven guidance in systems and network programming.
Dr. K. Erciyes is affiliated with the Dept. of Computer Engineering at Yasar University, Izmir, Türkiye.Among his Springer texts are Guide to Graph Algorithms and Guide to Distributed Algorithms.
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