## 1 Introduction  
In the last decades, the field of small satellite engineering has undergone a transformative evolution, reshaping space science, communications, Earth observation, and education. This revolution has been facilitated by the widespread availability and miniaturization of low-cost electronics, coupled with increased launch opportunities [1]. What was once solely the domain of governments and large organizations has now been democratized, with small companies, universities, and even low- and middle-income countries actively participating in satellite development [2]. Despite this progress, many satellite missions continue to face challenges, including delays, budget overruns, and sub-optimal performance. In particular, university CubeSat teams, struggle with issues such as high turnover rates, knowledge management, and balancing academic coursework with project responsibilities [3; 4]. In response to these challenges, there has been a growing interest in the adoption of Agile methodologies and Model-Based Systems Engineering (MBSE) techniques within the field of engineering and, more specifically, within the aerospace sector with small satellite design and development [5]. According to the International Council on Systems Engineering (INCOSE) [6; 7; 8], MBSE is the formalized application of modeling to support system requirements, design, analysis, verification and validation activities beginning in the conceptual design phase and continuing throughout development and later life cycle phases [9; 10; 11]. The impact and wide adoption of MBSE has led the community to even propose a roadmap that envisions that the \"future of system engineering is model-based\" to scale systems engineering by replacing document-oriented practices with models (see Figure 1). Some of the key concepts for Model-Based Systems Engineering are as follows [6; 7; 8; 9]:  
* Model-Centric Approach. This means that MBSE centralizes the development and documentation of systems around models, ensuring consistency and reducing redundancy. * System Life Cycle Coverage. MBSE supports all phases of the system life cycle, from requirements analysis and design to verification, validation, and maintenance. * Interdisciplinary Collaboration. Using MBSE facilitates a concurrent design process across different engineering disciplines by providing a common language and understanding of the system. * Traceability. MBSE enhances traceability between requirements, design, implementation, and testing, ensuring that all aspects of the system are aligned. * Analysis and Simulation. MBSE allows for early and continuous analysis and simulation, enabling engineers to identify and address issues early in the development process. The aforementioned key concepts are substantiated by the findings in the existing literature [6; 7; 8; 9; 12; 13] in this field, and have been integrated into well-established theoretical frameworks, such as those outlined by INCOSE [6; 7]. Specifically, the frameworks utilized include Object-Process Methodology (OPM) [14], which combines graphical and textual representations of system processes and objects, Systems Modeling Language (SysML) [15], which provides various diagrams to represent different system aspects, and Arcadia/Capella, which focuses on the definition and validation of system architecture. Regarding the issues faced, previous authors encountered several significant challenges, including dynamic requirements, interdisciplinary collaboration, traceability and integration, and documentation overhead [16]. Figure 1: INCOSE MBSE roadmap and future state. Compiled by the authors [6; 7; 8; 9]. These issues were addressed by combining Agile approaches with MBSE techniques. Agile methodologies were chosen for their iterative development, stakeholder participation, improved collaboration, and rapid response to change [17]. These methods provide iterative and adaptable procedures that enable quick responses to changing requirements and stakeholder feedback.