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

The Fifth Edition is available in PDF format from Software Diagnostics Services

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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.

Product information:

  • Title: Trace, Log, Text, Narrative, Data: An Analysis Pattern Reference for Information Mining, Diagnostics, Anomaly Detection, Fifth Edition
  • Authors: Dmitry Vostokov, Software Diagnostics Institute
  • Language: English
  • Product Dimensions: 21.6 x 14.0
  • Paperback: 400 pages
  • Publisher: OpenTask (March 2023)
  • ISBN-13: 978-1912636587

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