Egypt

Youssef

Advanced
@YoussefMostafaMohammed

The moment you ask why, you stop obeying the world and start learning from it

Common-API-VHAL. CommonAPI/SOME-IP bridge for Android Automotive 15 VHAL on Raspberry Pi 5. Solves C++ singleton duplication across shared library boundaries via centralized lifecycle management in the main VHAL executable, enabling seamless IPC between AOSP and Yocto/external ECUs.

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QuantumLog. A high-performance, multithreaded telemetry and logging system written in modern C++17. Designed for scalability, clarity, and control — combining the precision of quantum observation with the reliability of automotive-grade logging (vSOMEIP, DLT), with builds automated via Docker and continuous integration through Jenkins.

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docker-conan-jenkins-bazel-notes. Reproducible C++ builds with Docker and Conan. Learn how to manage dependencies, standardize environments, and ensure portable, reliable builds across machines and CI/CD pipelines. Includes examples using CMake, Conan, and Docker together.

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meta-games. games layers

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design-patterns-notes. A collection of classic design pattern implementations with explanations and example code, organized for easy learning and reference. Covers patterns like Strategy, Factory, Adapter, Observer, Decorator, Singleton, and more. Ideal for developers studying design patterns or preparing for interviews.

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modern-cpp-notes. This repository contains my personal study notes and practical examples for Modern C++ (C++11–C++23).

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GestureDetector. Gesture Detector

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cpp-template. cpp-template – A modern C++ project starter template integrating Docker, Conan and Bazel for reproducible builds, dependency management. Perfect for kickstarting scalable and maintainable C++ projects.

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embedded-c-notes. In-depth notes on Embedded C: memory layout, startup code, linker scripts, build process, and the real meaning of keywords like static, const, volatile, and register.

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Embedded-AI. A hands-on learning project demonstrating Embedded AI (TinyML) deployment on STM32F4 microcontrollers. Combines FreeRTOS real-time task scheduling with TensorFlow Lite Micro inference to run quantized neural networks directly on bare-metal edge devices.

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