PhD Student in Computer Science @ LSU
Software Reliability • Program Analysis • AI4SE
🌐 Website • 💼 LinkedIn • 📧 Email • 📄 arXiv • 🎓 Google Scholar
I study reliability challenges in mobile and AI-assisted software systems, advised by Dr. Umar Farooq at Louisiana State University. My work combines static program analysis and LLM benchmarking to detect defects and evaluate developer tools — across Android and mobile platforms.
Understanding and Detecting Platform-Specific Violations in Android Auto Apps
Moshood A. Fakorede, Umar Farooq
IEEE/ACM AST 2026 — Oral Presentation
Built AutoComply, a static analysis framework using a Car-Control Flow Graph (CCFG) to detect compliance violations in Android Auto apps. Detected 27 violations across 31 apps — 13× more than Android Lint — with zero false positives.
[DOI] [arXiv] [Code]
MobileDev-Bench: A Benchmark for Issue Resolution in Mobile Application Development
Moshood A. Fakorede, Krishna Upadhyay, A.B. Siddique, Umar Farooq
Under Review
A benchmark of 407 real-world issue-resolution tasks across 19 production mobile apps (Android, React Native, Flutter). Frontier LLMs achieve only 3.39–5.21% resolution rates, exposing a critical gap in mobile SE capability.
[arXiv] [Website] [Dataset]
Understanding Bugs in Quantum Simulators: An Empirical Study
Krishna Upadhyay, Moshood Fakorede, Umar Farooq
Under Review
[arXiv]
🔬 Program analysis and AI4SE research at LSU
💼 Open to Summer 2026 & 2027 internships — Software Engineering, Applied Science, GenAI