Solid C and C++ knowledge is a must to fully understand Windows diagnostic artifacts, such as memory dumps, and perform diagnostic, forensic, and root cause analysis beyond listing stack traces, DLLs, and driver information. This full-color reference book is a part of the Accelerated C & C++ for Windows Diagnostics training course organized by Software Diagnostics Services. The text contains slides, brief notes highlighting particular points, and illustrative source code fragments. The second edition added 45 Visual Studio projects with more than 5,500 lines of code. The book's detailed Table of Contents makes the usual Index redundant. We hope this reference is helpful for the following audiences:

C and C++ developers who want to deepen their knowledge
Software engineers developing and maintaining products on Windows platforms
Technical support, escalation, DevSecOps, cloud and site reliability engineers dealing with complex software issues
Quality assurance engineers who test software on Windows platforms
Security and vulnerability researchers, reverse engineers, malware and memory forensics analysts

�ber die Autorin bzw. den Autor:

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.

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