Accelerated Windows Debugging 4D: Training Course Transcript and WinDbg Practice Exercises, Fourth Edition

The full transcript of Software Diagnostics Services training with 16 step-by-step exercises, notes, and source code of specially created modeling applications. Learn live local and remote debugging techniques in the kernel, user process, and managed .NET spaces using the WinDbg debugger. The unique and innovative course teaches unified debugging patterns applied to real problems from complex software environments. The fourth edition was fully reworked and updated to use the latest WinDbg, added x64 disassembly review and Rust language to the existing and improved C/C++ and C# exercises.

Prerequisites: Working knowledge of one of these languages: C, C++, C#, Rust. Operating system internals and assembly language concepts are explained when necessary.

Audience: Software engineers, software maintenance engineers, escalation engineers, security and vulnerability researchers, malware and memory forensics analysts who want to learn live memory inspection techniques.

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 and Observability 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.