## 1 Introduction
### Language Interpreters and Virtual Machines in Embedded Systems  
One of the concepts of used language interpreters for dynamic code execution is that they usually generate a set of machine code-like instructions (often called \"bytecode\") instead of directly generating machine code for the targeted platform, which not only allows programmers to follow program execution instantly, but also to develop and deploy applications more efficiently, often in combination with agile practices. Even though these execution environments do not share common grammar, architecture, or program structures, most of them share some common examples, approaches, best practices, and algorithms for sufficient or acceptable portability and efficiency, as described in the research paper titled \"Design and Implementation of a Virtual Machine for a Dynamic Object-Oriented Programming Language\", which also describes Stella: a functional, procedural, class- and prototype-based object-oriented and modular general-purpose programming language developed to provide a flexible and scalable programming environment supporting both low- and high-level procedures, allowing for extension within other languages such as C, C++, or Java. Most of the virtual machine's existing concepts remain unchanged, though some adaptations to the native interface, bytecode serialization, and library integration for C and C++ projects were necessary to improve system efficiency, effectiveness, and compatibility [7]. Virtual machines (VMs) have become a key component of modern IT infrastructures, enabling efficient resource utilization, flexibility, and application isolation. However, their application to resource-constrained devices, such as embedded systems and microcontrollers, presents a significant bottleneck that requires careful consideration, with one primary challenge being the inherent limitations of processing and memory resources [13]. These devices are designed to be compact, energy-efficient, and cost-effective, often sacrificing processing power and memory capacity to achieve these features, which can seriously limit their ability to support virtual machines effectively. Implementing VMs as interpreters for microcontrollers involves addressing several key limitations:  
* Resource Constraints--This is usually the most emphasized and noticeable issue, as microcontrollers typically have limited processing power and memory capacity. Designed to be compact and energy-efficient, these devices often lack the RAM necessary for running complex applications or VMs efficiently. For example, a typical microcontroller averages 1 MB of RAM, which can be quickly exhausted by adding numerous libraries for communication protocols and data processing; a VM as an abstraction layer further increases the consumption of processing resources, leading to system instability and overheating. * Energy Consumption--Many embedded systems operate on batteries, making energy efficiency a crucial factor in their design and operation. The virtualization process can lead to increased energy consumption due to additional CPU and memory load. Studies show that virtualization increases energy consumption compared to traditional approaches, which can be particularly problematic for devices where extended battery life without frequent charging is essential [13; 14]. * Performance Issues--The additional load can also lead to increased latency and reduced responsiveness. Many systems have stringent real-time processing requirements, where delays can compromise the functionality of critical applications. Thus,managing the performance degradation caused by virtualization is necessary to ensure that systems meet their operational requirements. * Complexity and Maintenance Overhead: Implementing a VM layer in a microcontroller introduces additional complexity, both in terms of development and maintenance.