The full transcript of Software Diagnostics Services (former Memory Dump Analysis Services) training with 12 step-by-step exercises. Learn how to analyse app crashes and freezes, navigate through process core memory dump space and diagnose corruption, memory leaks, CPU spikes, blocked threads, deadlocks, wait chains, and much more. We use a unique and innovative pattern-driven analysis approach to speed up the learning curve. The training consists of practical step-by-step exercises using GDB and LLDB debuggers highlighting more than 30 memory analysis patterns diagnosed in 64-bit process core memory dumps. The training also includes source code of modelling applications written in Xcode environment, a catalogue of relevant patterns from Software Diagnostics Institute, and an overview of relevant similarities and differences between Windows and Mac OS X user space memory dump analysis useful for engineers with Wintel background. Audience: Software technical support and escalation engineers, system administrators, software developers, security professionals and quality assurance engineers.
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Dmitry Vostokov is an internationally recognized expert, speaker, educator, scientist, inventor, and author. He founded the pattern-oriented software diagnostics, forensics, and prognostics discipline (Systematic Software Diagnostics) and Software Diagnostics and Observability Institute. Vostokov has also authored over 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 over 30 years of experience in software architecture, design, development, and maintenance in various industries, including leadership, technical, and people management roles. Dmitry founded OpenTask Iterative and Incremental Publishing and Software Diagnostics Technology and Services (former Memory Dump Analysis Services). In his spare time, he explores Software Narratology and Quantum Software Diagnostics. His interest areas are theoretical software diagnostics and its mathematical and computer science foundations, application of formal logic, semiotics, 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 functional programming, cloud native computing, monitoring, observability, visualization, security, automation, applications of category theory to software diagnostics, development and big data, and diagnostics of artificial intelligence.
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