Memory Dump Analysis Anthology, Volume 12

Download or read book Memory Dump Analysis Anthology, Volume 12 written by Software Diagnostics Institute and published by . This book was released on 2021-12-28 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: This reference volume consists of revised, edited, cross-referenced, and thematically organized selected articles from Software Diagnostics 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 in December 2018 - November 2019 for software engineers developing and maintaining products on Windows and Linux platforms, quality assurance engineers testing software, technical support, escalation and site reliability engineers dealing with complex software issues, security researchers, reverse engineers, malware and memory forensics analysts. This volume is fully cross-referenced with volumes 1 - 11 and features: - 6 new crash dump analysis patterns with selected downloadable example memory dumps; - 2 pattern interaction case studies including Python crash dump analysis; - 16 new software trace and log analysis patterns; - Introduction to software pathology; - Introduction to graphical representation of software traces and logs; - Introduction to space-like narratology as application of trace and log analysis patterns to image analysis; - Introduction to analysis pattern duality; - Introduction to machine learning square and its relationship with the state of the art of pattern-oriented diagnostics; - Historical reminiscences on 10 years of trace and log analysis patterns and software narratology; - Introduction to baseplate representation of chemical structures; - WinDbg notes; - Using C++ as a scripting tool; - List of recommended Linux kernel space books; - Volume index of memory dump analysis patterns; - Volume index of trace and log analysis patterns.