SysMLv2: Advanced MBSE Language

Updated 16 October 2025

SysMLv2 is a comprehensive MBSE language with a formal semantic foundation that unifies system structure, behavior, and requirements.
It introduces built-in extensibility through formal specialization and redefinition, enabling systematic creation of domain-specific languages.
Its modular architecture, automated consistency checks, and natural language integration facilitate traceable and efficient model generation across lifecycles.

SysMLv2 (Systems Modeling Language version 2) is the forthcoming standard for model-based systems engineering (MBSE) that builds on and extends SysMLv1 by offering a formalized, integrated, and extensible semantic foundation. Unlike its predecessor, SysMLv2 is constructed as a precision language for representing the structure, behavior, requirements, and semantics of systems, enabling consistency, traceability, and automated analysis across system lifecycle models. It introduces advanced mechanisms for semantic concurrency, domain-specific extensions, and modularity that facilitate rigorous model-driven engineering (MDE) in complex, heterogeneous domains.

1. Formal Semantic Foundation and Unified System Model

SysMLv2 introduces a formal semantic metamodel—where every model element (block, requirement, flow, activity) is grounded in a precise abstract syntax and semantics. This is often realized via constructs such as the channel-based multi-queue structure-behavior coalescence process algebra (C-M-SBC-PA) metamodel, in which the system’s structural and behavioral views are projections of a unified, mathematically defined interaction transition graph:

$ITG = (Y, s_0, E, A, O, I, ITGR)$

where $Y$ is the state set, $s_0$ is the initial state, $E$ is the set of actors/blocks, $A$ channel names, $O$ parameter lists, $I$ blocks, and $ITGR$ the set of transitions (Chao, 2021).

This approach permits all SysML diagrams—internal block diagrams (IBD), state machine diagrams (SMD), activity diagrams (AD)—to be interpreted as different views derived from a common, formally defined system model. Projection algorithms parse and transform the ITG into diagram-specific relations, ensuring strict multi-view consistency. Such foundational unification is a significant advancement over prior standards where structural and behavioral constructs were only loosely coupled, or managed through separate sub-languages (Chao, 2021).

2. Language Extensibility and Creation of Domain-Specific Extensions

A central innovation in SysMLv2 is its built-in extensibility, which moves beyond UML-style profiling. The language allows direct specification of domain-specific extensions via formal mechanisms for specialization (":>") and redefinition (":>>").

For example, in the DarTwin DSL for Digital Twin system evolution, domain-specific concepts such as “Goal”, “Digital Twin”, and “Twin System” are defined as derived SysML elements, and a structured pattern for evolutionary transitions is modeled as:

#dartrans MyEvolution {
  #dartwin_core BaseModel { ... }
  #dartwin_before OldVersion :> BaseModel { ... }
  #dartwin_after NewVersion :> BaseModel { ... }
}

where the “:>” mechanism supports inheritance and enrichment, and the DSL’s user-defined keywords (e.g., “#digitaltwin”, “#goal”) are made natively part of the model library (Haugen et al., 14 Oct 2025). This extensibility enables systematic, traceable, and tool-chain-integrated DSL creation for specialized engineering domains and supports evolution management and reuse.

3. Modularization, Reuse, and Semantic Alignment

SysMLv2 is architected to support modular composition and semantic alignment of models. The language’s module and package system enables additive model construction, with new system elements or variants introduced in separate packages, preserving the integrity of the original design.

The alias construct allows for lightweight semantic mappings between elements, and the import mechanism (with public/private scoping) supports encapsulated reference of model fragments. This modularity is critical for collaborative MBSE, as it underpins “soft alignment” strategies in multi-organization model integration—facilitated by the ability to annotate relationships with custom metadata (e.g., “#FullyMatched”) and preserve traceability across autonomous models (Li et al., 22 Aug 2025).

A specialized LLM-assisted alignment approach leverages these constructs to iteratively extract model structure, suggest mappings, and verify semantic matches, supporting transactionally consistent soft alignment without forced model unification (Li et al., 22 Aug 2025).

4. Requirements Engineering and Traceability

Requirements modeling in SysMLv2 is enhanced by explicit formalization of requirements as constraints with Boolean satisfiability. The INCOSE-derived Model-Based Structured Requirements (MBSR) profile incorporates ISO/IEC/IEEE 29148 templates (e.g., [Subject] [Action] [Constraint] [Condition]) as structured properties, and encapsulates attributes and rules derived from the INCOSE Guide to Writing Requirements (Wheaton et al., 29 Jan 2024, Wheaton et al., 12 Oct 2024):

$\text{Requirement} = \text{[Subject]}\quad\text{[Action]}\quad\text{[Constraint]}\quad\text{[Condition]}$

These are directly embedded into the meta-model, supporting automated conformance checks (“satisfy”/“violate” relations), traceability matrices, and stakeholder review exports. The formal integration promotes model completeness, unambiguous specification, and automatable validation/verification (V&V), reducing ad hoc duplication and improving the Authoritative Source of Truth (ASoT) in MBSE environments (Wheaton et al., 29 Jan 2024, Wheaton et al., 12 Oct 2024).

5. Automated Consistency Checking and Model Validation

SysMLv2’s rigorous semantic foundation supports formal analysis and automated validation across system views. For example, the application of channel-based process algebra unifies consistency checks among structure, state, and activity diagrams (Chao, 2021). Tools and research frameworks (e.g., automated reasoners operating on condensed SysML XML) enable early detection of structural/functional inconsistencies, such as violation of energy or material conservation laws, misaligned input/output port types, and behavioral constraints (Chambers et al., 30 Jan 2025):

$\sum E_{\text{in}} = \sum E_{\text{out}}$

The use of curated functional knowledge bases and balance algorithms augments standard syntactic inspections, opening the path for integrating executable domain-specific constraints and physics-based reasoning directly into the system lifecycle model (Chambers et al., 30 Jan 2025).

6. Natural Language Integration and Model Generation

SysMLv2’s development is accompanied by an ecosystem of automation frameworks aimed at bridging informal domain knowledge and formal models. Multi-agent systems such as SysTemp decompose model generation into extraction, templating, completion, and syntactic validation, using LLMs and agent pipelines to turn natural language requirements into syntactically correct SysMLv2 code skeletons (Bouamra et al., 20 Jun 2025). This improves model generation quality even in the presence of sparse corpora and complex language syntax.

Similarly, pipelines that use NLP (tf-idf, OpenIE, WordNet) to extract entities and relationships enable the automated creation of Block Definition Diagrams, which are then mapped deterministically to computational code for simulation, closing the loop from text to formal model to executable system (Hendricks et al., 9 Jul 2025, Zhong et al., 2022). This supports parameterized abstraction and early-stage validation, impacting the efficiency and standardization of model creation.

7. Challenges and Future Directions

While SysMLv2 expands the language’s formalism, expressiveness, and automation potential, challenges persist in tooling—especially in rendering custom graphical notations and integrating domain-specific visual conventions as seen in the DarTwin DSL case studies (Haugen et al., 14 Oct 2025). Current implementations may suffer from non-deterministic auto-layouts, rendering inconsistencies, and lack of fine-grained visualization control, necessitating manual post-processing for domain-conformant diagrams.

The full realization of SysMLv2’s DSL extensibility, semantic analysis, and automated validation capabilities will depend on further advancements in model-based tooling, development of reference semantic libraries, and industry adoption of API standards for model transformation and integration.

Table: Selected Advancements in SysMLv2 and Implications

Advancement	Mechanism	Implication for MBSE
Formal, unified semantic metamodel	Channel-based ITG, algebraic projection	Consistent multi-view modeling, verification
Built-in extensibility for DSLs	Specialization (“:>”), redefinition (“:>>”)	Systematic DSL creation, domain support
Modular composition and alias/import	Package system, alias, import constructs	Scalable, traceable model integration
Requirements as explicit constraints	Structured slots, attributes, rules	Automatable V&V, improved traceability
Physics-based automated reasoning	Balance laws, KB-augmented reasoning	Early detection of physical inconsistencies
NLP/LLM-driven model generation	Agent pipelines, template generation	Accelerated, standardized model creation

SysMLv2 marks a shift from loosely coordinated, diagram-centric approaches to a language with deeply integrated semantics, extensibility, and automation, supporting digital engineering, multi-view modeling, traceable requirements management, and domain-specific innovations across complex system lifecycles.