Faiz Islamic Qowy

About Me

I am an undergraduate student in Informatics Engineering with a strong interest in Software Engineering, Machine Learning, and Computer Vision, as well as Formal Verification. My research explores topics such as data driven program analysis, microservice optimization, and code smell detection. I focus on developing tools and models that analyze software architecture, identify inefficiencies, and propose intelligent improvements for both traditional and machine learning-powered systems.

My goal is to pursue a PhD and advance research at the intersection of software engineering, machine learning, computer vision, and formal methods, contributing to more reliable, efficient, and impactful software systems.

Publication

1. Faiz Islamic Qowy; Muhammad Naufal Maulana; "Graph-Based Approach to Verifying Docker and Docker Compose Configurations"

2. Faiz Islamic Qowy; "Pengembangan Helioverify: Alat Verifikasi Formal Berbasis Satisfiability Modulo Theories Untuk Koreografis Dan Orkestrasi Microservices" (Bachelor Thesis) 

3. Dr. Sirajudin Noor, S.H., M.Kes; Faiz Islamic Qowy; "Deteksi Nutrisi Makanan Implementasi Computer Vision Untuk Aplikasi Mhealth Menggunakan Yolov8"

4. Faiz Islamic Qowy;. "Prefetching Cache Optimization Using Graph Neural Networks: A Modular Framework and Conceptual Analysis" arXiv

Projects

1. Solcheck

• Built a dual-layer analysis system combining SMT-based semantic checking and Slither static analyzer for comprehensive vulnerability detection.

• Developed a script-based interface for streamlined usage within smart contract development pipelines. 

• Tools used: Z3-Solver, Slither, Python 

2. Dockle 

• Developed tools to optimize Dockerfiles, achieving up to 50% reduction in image size and a 10% increase in application performance. 

• Enhancements led to faster builds, improved deployment efficiency, and easier management, all while maintaining full functionality 

• Tools used: C#, .NET

3. Scrappy  

• Built a custom data scraper using Selenium, enabling automated extraction of business data from Google Maps 

• Designed the tool to be configurable for different locations and search terms, supporting scalable and repeatable data gathering processes. 

• Tools used: JavaScript, Selenium