Overview

This short book is a full transcript of the Software Diagnostics Services seminar about physical memory analysis on desktop and server Windows platforms (a revised version of the previous seminars on complete crash and hang memory dump analysis). Topics include memory acquisition and its tricks, user vs. kernel vs. physical memory space, fiber bundle space, challenges of physical memory analysis, common WinDbg commands, memory analysis patterns and their classification, common mistakes, a hands-on WinDbg analysis example with logs, and a guide to further study. For this new edition, slides and their transcript text have been significantly revised, links and references have been checked and updated, and the whole WinDbg analysis session has been redone for Windows 10.

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9781912636808

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Dmitry Vostokov is an internationally recognized expert, speaker, educator, scientist, inventor, and author. He is the founder of pattern-oriented software diagnostics, forensics and prognostics discipline (Systematic Software Diagnostics), 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), Software Pathology, and Quantum Software Diagnostics. His current areas of interest are theoretical software diagnostics and its mathematical and computer science foundations, application of formal logic, 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, applications of category theory to software diagnostics, development and big data, and diagnostics of artificial intelligence.

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