This reference volume consists of revised, edited, cross-referenced, and thematically organized selected articles from Software Diagnostics and Observability Institute (DumpAnalysis.org + TraceAnalysis.org) and Software Diagnostics Library (former Crash Dump Analysis blog, DumpAnalysis.org/blog) about software diagnostics, root cause analysis, debugging, crash and hang dump analysis, software trace and log analysis written from 15 April 2024 to 14 November 2025 for software engineers developing and maintaining products on Windows platforms, quality assurance engineers testing software, technical support, DevOps and DevSecOps, escalation and site reliability engineers dealing with complex software issues, security and vulnerability researchers, reverse engineers, malware and memory forensics analysts, data science and ML/AI researchers and engineers. This volume is fully cross-referenced with volumes 1 - 16 and features: - 6 new crash dump analysis patterns- 11 new software trace and log analysis patterns- Introduction to pattern-oriented observability- Introduction to software morphology- Introduction to geometric theory of traces and logs- Introduction to pattern-oriented intelligence and AI- Introduction to agentic narratology and workflow diagnostic pattern language- Introduction to algebra of prompting and context management pattern language- Logics of memory dump and trace analysis- Introduction to pattern-oriented system logic- Introduction to ontological diagnostics- Machine learning as memory dump analysis- The stomach metaphor for AI and pattern metabolism- OS internals and category theory- Introduction to pattern category theory- Meta-diagnostic and categorical unification of software diagnostics and digital pathology- A Lego model as an autoencoder and Lego disassembly as tokenization- Memoidealism as a post-computational philosophy of AI- Lists of recommended booksThe primary audience for Memory Dump Analysis Anthology reference volumes (Diagnomicon) is software engineers developing and maintaining products on Windows and Linux platforms, technical support, escalation, and site reliability engineers dealing with complex software issues, quality assurance engineers testing software, security and vulnerability researchers, reverse engineers, malware and memory forensics analysts, data scientists, ML and AI researchers and engineers.
