Memory Thinking for C & C++ Linux Diagnostics (Paperback)

Dmitry Vostokov

ISBN 10: 1912636565 / ISBN 13: 9781912636563

Published by Opentask, 2025

About this Item

Paperback. Solid C and C++ knowledge is a must to fully understand Linux diagnostic artifacts, such as core memory dumps, and perform diagnostic, forensic, and root cause analysis beyond listing backtraces. This full-color reference book is a part of the Accelerated C & C++ for Linux Diagnostics training course organized by Software Diagnostics Services. The text contains slides, brief notes highlighting particular points, and source code illustrations. In addition to new topics, the second edition adds 45 projects with more than 5,500 lines of code. The book's detailed Table of Contents makes the usual Index redundant. We hope this reference is helpful for the following audiences: C and C++ developers who want to deepen their knowledgeSoftware engineers developing and maintaining products on Linux platformsTechnical support, escalation, DevSecOps, cloud and site reliability engineers dealing with complex software issuesQuality assurance engineers who test software on Linux platformsSecurity and vulnerability researchers, reverse engineers, malware and memory forensics analysts Solid C and C++ knowledge is a must to fully understand Linux diagnostic artifacts, such as memory dumps. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9781912636563

Bibliographic Details

• Title: Memory Thinking for C & C++ Linux Diagnostics (Paperback)
• Publisher: Opentask
• Publication Date: 2025
• Language: English
• ISBN 10: 1912636565
• ISBN 13: 9781912636563
• Binding: Paperback
• Edition: 2nd Edition
• Condition: new

About this title

Synopsis

Solid C and C++ knowledge is a must to fully understand Linux diagnostic artifacts, such as core memory dumps, and perform diagnostic, forensic, and root cause analysis beyond listing backtraces. This full-color reference book is a part of the Accelerated C & C++ for Linux Diagnostics training course organized by Software Diagnostics Services. The text contains slides, brief notes highlighting particular points, and source code illustrations. In addition to new topics, the second edition adds 45 projects with more than 5,500 lines of code. The book's detailed Table of Contents makes the usual Index redundant. We hope this reference is helpful for the following audiences:

• C and C++ developers who want to deepen their knowledge
• Software engineers developing and maintaining products on Linux platforms
• Technical support, escalation, DevSecOps, cloud and site reliability engineers dealing with complex software issues
• Quality assurance engineers who test software on Linux platforms
• Security and vulnerability researchers, reverse engineers, malware and memory forensics analysts

About the Author

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.