About the Book
This book is a revised edition of the original Accelerated Windows Software Trace Analysis training course. General trace and log analysis pattern language covers any execution artifact from a small debugging trace to a distributed log with billions of messages from hundreds of computers, thousands of software components, threads, and processes. It also allows the application of uniform diagnostics and anomaly detection across diverse software environments, troubleshooting and debugging Windows, Mac OS X, Linux, Android, iOS, and any other possible computer platform including networking and IoT. Part 1 covers fundamentals and explains more than 60 basic trace and log analysis patterns, which are now cross-referenced in this improved and less Windows-centric edition. It can also serve as a reference.
About the Author
Dmitry Vostokov is an internationally recognized expert, speaker, educator, scientist and author. He is the founder of pattern-oriented software diagnostics, forensics and prognostics discipline 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), and Software Pathology. His current areas of interest are theoretical software diagnostics and its mathematical and computer science foundations, application of 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, and applications of category theory to software development and big data.