Computational and Experimental Evaluation of Secure Firmware Development Using Rust and AI‑Driven DevOps Automation - Lalith Lakshmi Chaitanya Kumar Mangalagiri (International Journal of Computational and Experimental Science and Engineering, 2025)
This study presents a computational and experimental evaluation of secure firmware development using the Rust programming language integrated with AI‑driven DevOps automation. Modern firmware engineering continues to face challenges related to memory‑safety defects, multi‑architecture build complexity, and manual continuous‑integration configuration. To address these issues, the proposed framework combines Rust’s ownership‑based compile‑time safety guarantees with multi‑target cross‑compilation pipelines for x86‑64 and ARM, QEMU‑based hardware‑in‑the‑loop simulation, and machine‑learning‑assisted automation incorporating gradient‑boosted decision trees, natural language processing techniques, and multi‑agent orchestration for pipeline synthesis, compliance prediction, and diagnostic analysis. Experimental validation was performed using Azure DevOps infrastructure and included systematic benchmarking with paired t‑tests (n = 30 per configuration), bootstrap confidence intervals (10,000 iterations), and coefficient of variation analysis to ensure statistical robustness. The evaluation integrates cargo‑based testing, QEMU emulation, and automated performance‑regression detection.Results demonstrate complete elimination of memory‑safety vulnerabilities in Rust components, a 90–95% reduction in developer onboarding time, a 75–85% decrease in build failure‑resolution effort, and performance parity with optimized C++ implementations (p < 0.05). Reliability also improved, with defect‑escape rates approaching zero during production deployment. Overall, the findings validate Rust’s suitability for security‑critical firmware and highlight the engineering benefits of incorporating AI‑assisted DevOps workflows. The study provides reproducible computational methods, experimental protocols, and implementation patterns for organizations seeking scalable, memory‑safe, and automated firmware development practices.