Publications & Books
The Zero Point Laws: A Reverse Engineering Odyssey | The Zero Point Laws is not just another book about coding—it’s a manifesto for understanding, repairing, and evolving complex systems when documentation is missing, legacy code is crumbling, and chaos seems inevitable. Karl G. Zafiris, an engineer, architect, and systems thinker, takes you on a reverse-engineering odyssey through the hidden laws that govern software systems. Instead of chasing perfection, the Zero Point Laws (ZPL) offer a framework built on adaptability, clarity, and resilience. Through principles like the Law of Entry Points (“A system without a clear door is just a maze”) and the Law of Binding (“Time is the only resource your system will always demand more of”), ZPL challenges you to think differently about legacy code, complexity, and human factors in engineering. Blending technical insight with philosophical depth, this book reveals: Why adaptability matters more than perfection.
Practical PHP: Principles & Conventions | This book features certain development principles and conventions of programming, teaching the reader initial models and definitions. After the swift introduction of several programming concepts such as pseudo-code, divide and conquer and the definition of a problem, the reader will attempt to become familiar with the popular scripting web language, PHP. PHP's a powerful general purpose programming language that's mainly used for web development, database interaction and cross application development. Seventy percent of the world wide web is built using PHP since the explosion of the free internet.
Contextual AI Chatbot Development in Assisted Living Environments | This thesis aims to study and analyze the measurements extracted from a group of sensors in the home within ESDALAB. In particular, the collected values from external APIs referring to meteorological parameters and the return of values according to the specified location. The measurements will also be extracted from a pressure sensor to identify the user's seating during his stay in the smart home. Then, the data will be collected and the results will be processed and structured for use in the Kalliope framework. Data sets collected from all remote interfaces will be smoothed (where necessary) and used in machine learning algorithms either for prediction estimates or for classification of results.