Table of Contents

Chapter 1: Fundamental Vocabulary.- Chapter 2: Pattern-Oriented Debugging.- Chapter 3: Elementary Diagnostics Patterns.- Chapter 4: Debugging Analysis Patterns.- Chapter 5: Debugging Implementation Patterns.- Chapter 6: IDE Debugging in Cloud.- Chapter 7: Debugging Presentation Patterns.- Chapter 8: Debugging Architecture Patterns.- Chapter 9: Debugging Design Patterns.- Chapter 10: Debugging Usage Patterns.- Chapter 11: Case Study: Resource Leaks.- Chapter 12: Case Study: Deadlock.- Chapter 13: Challenges of Python Debugging in Cloud Computing.- Chapter 14: Challenges of Python Debugging in AI and Machine Learning.- Chapter 15: What AI and Machine Learning Can Do for Python Debugging.- Chapter 16: The List of Debugging Patterns.

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 Institute (DA+TA: DumpAnalysis.org + TraceAnalysis.org). Vostokov has also authored multiple 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 thirty years of experience in software architecture, design, development, and maintenance in various industries, including leadership, technical, and people management roles. In his spare time, he presents multiple topics on Debugging.TV and explores Software Narratology and its further development as Narratology of Things and Diagnostics of Things (DoT), Software Pathology, and Quantum Software Diagnostics. His current interest areas 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 artificial intelligence diagnostics.