About the Book
This training course is a Linux version of the previous Practical Foundations of Windows Debugging, Disassembly, Reversing book. It also complements Accelerated Linux Core Dump Analysis training course.
Although the book skeleton is the same as its Windows predecessor, the content was revised entirely because of a different operating system, debugger (GDB), toolchain (GCC, assembler, linker), application binary interface, and even an assembly language flavor, AT&T.
The course is useful for:
- Software technical support and escalation engineers
- Software engineers coming from JVM background
- Software testers
- Engineers coming from non-Linux environments, for example, Windows or Mac OS X
- Linux C/C++ software engineers without assembly language background
- Security researchers without assembly language background
- Beginners learning Linux software reverse engineering techniques
This book can also be used as x64 assembly language and Linux debugging supplement for relevant undergraduate level courses.
About the Author
Dmitry Vostokov is an internationally recognized expert, speaker, educator, scientist and author. He is the founder of pattern-oriented software diagnostics, forensics and prognostics discipline and Software Diagnostics Institute. Vostokov has also authored more than 50 books on software diagnostics, anomaly detection and analysis, software and memory forensics, root cause analysis and problem solving, memory dump analysis, debugging, software trace and log analysis, reverse engineering and malware analysis. He has more than 25 years of experience in software architecture, design, development and maintenance in a variety of industries including leadership, technical and people management roles. Dmitry also founded Syndromatix, Anolog.io, BriteTrace, DiaThings, Logtellect, OpenTask Iterative and Incremental Publishing and Software Diagnostics Technology and Services (former Memory Dump Analysis Services) and Software Prognostics. In his spare time, he presents various topics on Debugging TV and explores Software Narratology, its further development as Narratology of Things and Diagnostics of Things (DoT), and Software Pathology. His current areas of interest are theoretical software diagnostics and its mathematical and computer science foundations, application of artificial intelligence, machine learning and data mining to diagnostics and anomaly detection, software diagnostics engineering and diagnostics-driven development, diagnostics workflow and interaction. Recent interest areas also include cloud native computing, security, automation, functional programming, and applications of category theory to software development and big data.