Software Diagnostics, Observability, and Debugging Crosswords
$22.81
- Paperback
108 pages
- Release Date
16 October 2026
Summary
Software diagnostics has its own vocabulary. We use it to describe execution artifacts, recognize diagnostic patterns, and communicate our findings. Crosswords provide another way to revisit this vocabulary, recall familiar concepts, and discover gaps in our knowledge.
In this book, I bring together twenty-four crosswords covering software diagnostics, observability, and debugging. Separate puzzles explore Windows, Linux, and macOS memory dump vocabulary, followed by memory dump analy…
Book Details
| ISBN-13: | 9781919135045 |
|---|---|
| ISBN-10: | 1919135049 |
| Author: | Dmitry Vostokov |
| Publisher: | Opentask |
| Imprint: | Opentask |
| Format: | Paperback |
| Number of Pages: | 108 |
| Release Date: | 16 October 2026 |
| Weight: | 204g |
| Dimensions: | 7mm x 152mm x 229mm |
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Dmitry Vostokov
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 the Software Diagnostics and Observability Institute.
Vostokov has 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 across various industries, holding leadership, technical, and people management roles.
Dmitry founded OpenTask Iterative and Incremental Publishing and Software Diagnostics Technology and Services.
In his spare time, he explores Software Narratology, Software Pathology, Software Morphology, Quantum Software Diagnostics, and Pattern-Oriented AI. His areas of interest include:
- 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.
- Functional programming, cloud native computing, monitoring, observability, visualization, security, and automation.
- Applications of category theory to software diagnostics, development, and big data.
- Diagnostics of artificial intelligence.
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