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This reference volume consists of revised, edited, cross-referenced, and thematically organized articles from Software Diagnostics Institute and Software Diagnostics Library (former Crash Dump Analysis blog) written in August 2006 – December 2007. This major revision updates tool information and links with ones relevant for Windows 10 and removes obsolete references. Some articles are preserved for historical reasons, and some are updated to reflect the debugger engine changes. Most of the content, especially memory analysis pattern language, is still relevant today and for the foreseeable future. Crash dump analysis pattern names are also corrected to reflect the continued expansion of the catalog. The primary audience for Memory Dump Analysis Anthology reference volumes is: software engineers developing and maintaining products on Windows platforms, technical support, escalation, and site reliability engineers dealing with complex software issues, quality assurance engineers testing software on Windows platforms, security and vulnerability researchers, reverse engineers, malware and memory forensics analysts.
Author Biography
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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