Accelerated Linux API for Software Diagnostics: With Category Theory in View

by Dmitry Vostokov, Software Diagnostics Services

Overview

The book contains the full transcript of Software Diagnostics Services training with 16 hands-on exercises on various topics related to Linux API. Knowledge of Linux API is necessary for:

• Development
• Malware analysis
• Vulnerability analysis and exploitation
• Reversing
• Diagnostics
• Debugging
• Memory forensics
• Crash and hang analysis
• Secure coding
• Static code analysis
• Trace and log analysis

The training uses a unique and innovative pattern-oriented analysis approach and provides:

• Overview
• Classification
• Patterns
• Internals
• Development examples
• Analysis examples
• Comparison with Windows API

Product Details

ISBN-13:	9781912636624
Publisher:	Opentask
Publication date:	08/04/2023
Series:	Linux Internals Supplements
Pages:	234
Product dimensions:	8.50(w) x 11.00(h) x 0.61(d)

About the Author

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.