microcontroller programming

This study systematically evaluates whether Rust can compete with C in performance and resource efficiency for microcontroller firmware development and assesses its industrial viability. Two teams independently implemented identical industrial IoT firmware—one in Rust and the other in C—and key metrics including development effort, memory footprint, and execution speed were compared on real hardware. This work presents the first systematic comparison of the two languages in a genuine industrial context and introduces Ariel OS, a lightweight Rust-based runtime. Empirical results demonstrate that Rust matches or exceeds C in both resource utilization and execution performance, while Ariel OS exhibits a smaller binary footprint, collectively establishing Rust as a reliable and competitive choice for microcontroller firmware development.

Embedded systems face significant challenges in hardware-software co-development, including strong hardware dependencies, stringent real-time and safety requirements, and poor compatibility with conventional CI/CD practices. Method: Through a systematic literature review of 20 academic and industrial studies, we establish the first DevOps practice taxonomy specifically for embedded systems; propose a hardware-aware CI/CD framework supporting closed-loop hardware testing, resource-constrained execution, and safety compliance; and identify and address critical gaps in deployment automation and observability. Contribution/Results: We synthesize toolchain design, automated testing strategies, pipeline lightweighting, and firmware security practices into a structured knowledge framework. This work provides both a theoretical foundation and concrete research directions for academia, and delivers a reusable, industry-applicable methodology for realizing Embedded DevOps.

Debugging embedded programs is notoriously challenging due to tight software-hardware coupling, and existing tools often rely on external hardware probes or serial logging, resulting in low efficiency. This work proposes Inline, a novel programming tool that, for the first time, enables real-time inline visualization of hardware logs directly within source code. It introduces a domain-specific expression language to support programmable manipulation of logs, allowing developers to intuitively trace execution flow and precisely localize faults. Seamlessly integrated into standard embedded development environments, Inline significantly lowers the barrier to effective debugging. A user study with twelve participants demonstrates marked improvements in both debugging efficiency and accuracy when using the tool.

To address the low efficiency and error-proneness of manual development and integration of software components in embedded systems, this paper proposes an Abstract Syntax Tree (AST)-driven Retrieval-Augmented Generation (RAG) method for fully automated, zero-intervention generation and formal verification of microcontroller Hardware Abstraction Layer (HAL) code. Focusing on the STM32F407 GPIO module, the approach integrates AST-based semantic analysis, RAG-enabled dynamic knowledge retrieval, static code verification, and HAL framework adaptation to ensure syntactic correctness, semantic consistency, and platform compatibility. Experimental evaluation demonstrates that the generated HAL code is functionally complete, directly compilable and flashable, and passes comprehensive functional testing on real hardware across all operational scenarios, achieving 98.7% accuracy. This work establishes the first end-to-end pipeline for automated HAL code generation coupled with formal verification in embedded systems.

Embedded IoT system development faces significant challenges, including high cross-domain expertise barriers, heavy manual effort, low efficiency, and error-proneness. To address these, this paper proposes the first end-to-end automated embedded IoT software development framework, integrating large language models (LLMs) with domain-specific embedded knowledge to enable fully autonomous hardware-in-the-loop development. Our key contributions are: (1) a component-aware library parsing method; (2) a domain-knowledge-injected library knowledge generation mechanism; and (3) an automatic programming paradigm ensuring reliable deployment. We evaluate the framework across 71 modules, four hardware platforms, and over 350 tasks. Results show a code accuracy of 95.7% and an end-to-end task success rate of 86.5%, outperforming human experts by up to 53.4% in task completion.

This work addresses the lack of cost-effective, high-precision power measurement solutions for embedded systems, given the high expense and inflexibility of industrial semiconductor test equipment. The authors propose and implement a compact, open-source hardware and software-based system-level power profiling platform that integrates a Raspberry Pi controller, a high-accuracy current sensor, and a microcontroller-based device under test (DUT). A lightweight HTTP interface enables automated firmware deployment, synchronized execution, and remote control. By uniquely combining low-cost open-source hardware with an automated testing workflow, the platform achieves high-resolution current acquisition and supports energy-efficiency benchmarking and regression testing across multiple firmware variants. This significantly enhances the scalability, reproducibility, and practicality of power analysis for embedded systems, making it well-suited for research, prototyping, and educational applications.

This work addresses the debugging gap between high-level functional reactive programming (FRP) abstractions and their low-level C/C++ implementations in Emfrp, where debugging traditionally requires inspecting generated code. To bridge this gap, the authors propose a multi-modal debugging framework that precisely maps Emfrp language constructs to their corresponding locations in compiled code using source-code mapping techniques. The framework integrates multi-level debugging interfaces with embedded systems, enabling coordinated debugging across the FRP abstraction layer and platform-specific I/O layers. It maintains compatibility with conventional debuggers such as GDB and supports cross-language debugging. Experimental evaluation on the ESP32 microcontroller demonstrates that the approach significantly improves debugging efficiency for FRP-based embedded applications.

This work addresses the challenge of detecting architectural drift—discrepancies between design-time architecture and runtime behavior—in long-lived embedded firmware. The authors propose a practical, hardware-assisted detection approach that captures runtime execution traces, abstracts them into inter-component message interaction sequences, and performs deterministic comparison against design-phase UML sequence diagrams to precisely identify confirmed, missing, extraneous, or inverted behavioral deviations. To facilitate expert review, the method further leverages a constrained large language model to generate human-readable explanatory reports. Integrating runtime trace analysis, deterministic architectural conformance checking, and constraint-guided LLM-based explanation generation for the first time, the approach demonstrates high agreement with expert annotations across 26 industrial cases, substantially reducing manual analysis effort while effectively supporting ISO 26262 safety documentation requirements.