Trace, Log, Text, Narrative, Data: An Analysis Pattern Reference for Information Mining, Diagnostics,...

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Dmitry Vostokov Software Diagnostics Institute

Trace, Log, Text, Narrative, Data

An Analysis Pattern Reference for Information Mining, Diagnostics, Anomaly Detection, Fifth...

Dmitry Vostokov, Software Diagnostics Institute

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English

Opentask
26 November 2023

Computer security; Computer networking & communications; Computer science

General trace and log analysis patterns allow the application of uniform diagnostics and anomaly detection across diverse software environments. This 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. Pattern-oriented trace and log analysis is applicable to troubleshooting and debugging Windows, macOS, Linux, FreeBSD, Android, iOS, z/OS, and any other possible computer platform, including networking and IoT. Its pattern catalog is a part of pattern-oriented software data analysis, diagnostics, anomaly detection, forensics, prognostics, root cause analysis, and debugging developed by Software Diagnostics Institute. Also, the scope of applicability of such analysis patterns is much wider than just software execution artifacts or temporal data and now includes general data, narratives, text, and image analysis (space-like narratology). This reference reprints with corrections almost 230 patterns originally published in Memory Dump Analysis Anthology volumes 3 - 14 and Software Diagnostics Library. It also includes additional 19 analysis patterns from the forthcoming volume 15, bringing the total analysis pattern count to 229. Full-color diagrams accompany almost all pattern descriptions. The fifth edition includes 28 more patterns, updated diagram pictures, classification, and the list of narratological and mathematical influences, and now includes the long-awaited introduction and two new appendixes.

By: Dmitry Vostokov, Software Diagnostics Institute
Imprint: Opentask
Edition: 5th ed.
Dimensions: Height: 216mm, Width: 140mm, Spine: 26mm
Weight: 644g
ISBN: 9781912636587
ISBN 10: 1912636581
Pages: 402
Publication Date: 26 November 2023
Audience: General/trade , ELT Advanced
Format: Paperback
Publisher's Status: Active

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), 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 development and big data, and diagnostics of artificial intelligence.