ORCUS - Cameo Plug-In for Meta-Model Compliance

Model-Based Systems Engineering MBSE Cameo Systems Modeler Model Compliance Meta-Model Verification Validation Model Federation Interoperability SysML

Enforcing compliance to program- or organization-defined meta-models for model-based systems engineering (MBSE) continues to be a challenge due to the standard practice of manual review for compliance and the timing of these compliance reviews after the bulk of the modeling effort has already been completed. This approach often leads to rework, which becomes a significant time and cost factor late in the model development life cycle. More likely still is that there is no complete validation of the models against the established meta-model(s) due to the amount of time and effort involved. This in turn increases the likelihood that models will be neither interoperable nor support consistent analysis, key intentions of having a shared meta-model implemented across separate models. Easing user compliance with these meta-models may address these concerns directly, decrease the overall costs of model development and review, and improve the technical and cultural adoption of MBSE. The Johns Hopkins University Applied Physics Laboratory (JHU/APL) developed a plug-in for Cameo Systems Modeler, a common MBSE modeling tool, which provides a more consistent and interactive method to comply with pre-defined Systems Modeling Language (SysML) meta-models than currently exists. This plug-in, named ORCUS (Object Recognition for Compliance, Usability, and Sustainment), provides both Active Validation to aid users as they model and a holistic project Discrete Validation, which can be used for reviews of modeling compliance. The Active Validation capability integrates into the existing Cameo user interface to provide a seamless user experience within the native Cameo environment. This helps to reduce the learning curve associated with Cameo Systems Modeler tools, as well as serve as a best-practice training tool for new users, while increasing effectiveness and efficiency for all Cameo modelers, experienced or new. The user loads user-defined meta-model(s), and ORCUS reads through the meta-model elements to find all rules defined using a set of custom ORCUS stereotypes. Afterwards, whenever an element is created or manipulated, ORCUS compares the element to all rules that apply to that element,and provides suggestions on how to comply with each of the rules outlined in the meta-model. The Discrete Validation capability produces exportable metrics that describe the state of compliance for a given model, which can be used for status reporting or model review. Discrete Validation checks all elements in a Cameo project (model) against the rules defined in the meta-model and is able to produce tabular reports within the Cameo model or as a Comma-Separated Values (CSV) spreadsheet file. ORCUS developers intend that Discrete Validation be applied to pre-existing models to establish state of compliance prior to using the Active Validation feature. However, Discrete Validation can also serve as a final verification of both new and pre-existing models to ensure compliance with all relevant meta-models. Cameo Systems Modeler has a native validation suite with some default checks of model fidelity and the capability to add additional scripted validation checks. This is sufficient for many applications of modeling standards and simple meta-model rules, but it exists separately from the reference meta-models which it is intended to represent. Consequently, this allows for the introduction of errors in interpretation and gaps between the meta-model and the validation rules. Using this form of validation can also limit the complexity of the rules being defined. ORCUS solves the first of these problems by directly using the meta-model in interpreting the rules, removing any human step in conversion from meta-model to rules. Additionally, ORCUS allows for semi-complex rulesets to enhance the utility of the meta-models and ensure useful compliance to the meta-model. While ORCUS does not ensure that the model content is correct, it does ensure that the content is correctly modeled in adherence to established modeling standards. This can decrease the labor and schedule costs associated with integrating federated models, allow for faster development of high-fidelity interoperable models, serve as an active training tool by providing modeling recommendations and helping users understand established standards, and decrease the overall maintenance costs of Cameo models.