The full-color transcript of Software Diagnostics Services training. Learn how to analyze Linux process and kernel crashes and hangs, navigate through core memory dump space and diagnose corruption, memory leaks, CPU spikes, blocked threads, deadlocks, wait chains, and much more. This training uses a unique and innovative pattern-oriented diagnostic analysis approach to speed up the learning curve. The training consists of more than 70 practical step-by-step exercises using GDB and WinDbg debuggers, highlighting more than 50 memory analysis patterns diagnosed in 64-bit core memory dumps from x64 and ARM64 platforms. The training also includes source code of modeling applications, a catalog of relevant patterns from the Software Diagnostics Institute, and an overview of relevant similarities and differences between Windows and Linux memory dump analysis useful for engineers with a Wintel background. In addition to various improvements, the fully revised and updated fourth edition adds entirely new material, such as defect mechanism patterns and WinDbg Linux kernel dump analysis exercises.

About the Author

Dmitry Vostokov is an internationally recognized expert, speaker, educator, scientist, inventor, and author. He founded the pattern-oriented software diagnostics, forensics, and prognostics discipline (Systematic Software Diagnostics) and Software Diagnostics Institute. Vostokov has also authored over 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 over 30 years of experience in software architecture, design, development, and maintenance in various industries, including leadership, technical, and people management roles. Dmitry founded OpenTask Iterative and Incremental Publishing and Software Diagnostics Technology and Services (former Memory Dump Analysis Services). In his spare time, he explores Software Narratology and Quantum Software Diagnostics. His interest areas are theoretical software diagnostics and its mathematical and computer science foundations, application of formal logic, semiotics, 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 functional programming, cloud native computing, monitoring, observability, visualization, security, automation, applications of category theory to software diagnostics, development and big data, and diagnostics of artificial intelligence.

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