Model-Based Systems Engineering (MBSE) is transforming the way safety-critical software systems are designed, analyzed, and validated. By leveraging formal models throughout the lifecycle, MBSE aims to improve traceability, consistency, and early detection of design flaws. However, implementing MBSE in industries such as aerospace, automotive, and medical devices—where software failures can be catastrophic—presents unique challenges. This article dissects the major obstacles encountered and outlines best practices for maximizing safety through MBSE techniques.
Major Obstacles in Implementing MBSE for Safety-Critical Code
One of the prominent challenges in deploying MBSE for safety-critical software is the integration of models with legacy systems and processes. Many organizations have deeply entrenched workflows and toolchains oriented around document-centric or code-centric development. Migrating to MBSE demands significant changes, which can lead to resistance from stakeholders, compatibility issues with existing assets, and the risk of disrupting ongoing projects that rely on traditional methodologies.
Another significant obstacle is the complexity of ensuring comprehensive traceability and verifiability from high-level models down to implementation and testing. Safety standards such as DO-178C, ISO 26262, or IEC 62304 mandate strict traceability between requirements, design, code, and tests. Translating these requirements into actionable MBSE artifacts, and maintaining traceability across multiple levels of abstraction, can be labor-intensive and error-prone without mature tool support and well-defined processes.
Lastly, there is a knowledge and skills gap among engineers and teams tasked with safety-critical development. MBSE demands proficiency in modeling languages (e.g., SysML, UML), formal methods, and specialized tools. The steep learning curve can impede adoption, as teams may struggle to model complex behaviors accurately or fail to leverage the full capabilities of MBSE tools, ultimately undermining the safety objectives MBSE is meant to enhance.
Proven Strategies to Enhance Safety with MBSE Approaches
To address integration challenges, organizations should adopt an incremental MBSE deployment strategy. This involves piloting MBSE in targeted subsystems or new projects, establishing interfaces with legacy tools, and gradually expanding MBSE practices organization-wide. Such an approach allows teams to demonstrate value, build confidence, and iteratively refine workflows without disrupting critical ongoing efforts, ensuring a smoother transition and better buy-in from all stakeholders.
Ensuring robust traceability and verifiability requires leveraging toolchains capable of automatic linkage among requirements, models, code, and test artifacts. Best practices include defining clear modeling guidelines, using standardized profiles for safety, and applying automated analysis and validation checks. Consistency and completeness can be further enforced by integrating MBSE tools with requirements management and verification platforms, supporting audits, and facilitating compliance with safety standards.
To bridge the skills gap, organizations should invest in sustained training and foster a modeling culture. Establishing MBSE centers of excellence, encouraging certification in modeling languages, and creating mentoring programs can help build internal expertise. Equally important is involving safety engineers early in modeling activities, promoting cross-disciplinary collaboration, and ensuring that safety considerations are systematically embedded into models from the outset.
The adoption of MBSE in safety-critical software environments presents both technical and organizational challenges, from legacy integration to skill development and rigorous traceability. However, by applying thoughtful strategies—such as incremental rollout, tool-supported traceability, and ongoing upskilling—organizations can unlock the full potential of MBSE. Ultimately, these best practices not only address regulatory requirements but also contribute to building safer, more reliable software systems in mission- and life-critical domains.
