Integrating MBSE into a Multi-Disciplinary Engineering Environment A Software Engineering Perspective Mark Hoffman 20 June 2011 Copyright © 2011 by Lockheed Martin Corporation. Published and used by INCOSE with permission.

Background Large Systems Integration that includes large scale distributed S/W systems 100’s of system and software engineers Over a 100 Components Hardware components and software components (CSCIs) Well over 1 million lines of code 100’s of Hw / Sw Interfaces 1000’s of Requirements Engineering disciplines use multiple languages and tools whose results are not always easily integrated The potential for MBSE is that it provides a means to integrate multi-disciplinary engineering including systems, hardware, software, analysis, and test throughout the development life cycle

Software Engineering is mostly Model Based Software Development Current Approach Software Engineering is mostly Model Based Software Development SysML models – requirement analysis UML models and Matlab/Simulink models – design & implementation Systems Engineering flow down of System Design, Interfaces and Requirements to Software Engineering typically consists of Textual Documentation Word Documents, PowerPoint slides, Excel spreadsheets, email, etc.

Lack of integration is a source of design discrepancies and errors Problem Lack of integration is a source of design discrepancies and errors As design, interfaces or requirements change integration issues are introduced Time lag for information Coordination of changes showing up at the same time Often manually intensive to gather up the changes and get distributed to the stake holders

Considerations For Incorporating MBSE Approach Incorporation of MBSE into a broader multi-disciplinary engineering environment could provide More timely information Similar semantics using standards like SysML Easier integration with Software Modeling Tighter integration to improved traceability Requirements System model artifacts such as interfaces Test Cases – System scenarios (Activity Diagrams) Impact Analysis

Questions to be addressed with an MBSE Approach – (1) What should other engineering disciplines expect from MBSE? Software engineering should expect the high level conops of the system (mission scenarios) How the system will be used Software engineering should expect interface definitions including component channelization Software engineering should expect change impact due to requirement changes that effect software

Questions to be addressed with an MBSE Approach – (2) What can MBSE learn from model-based approaches used in other engineering disciplines? MBSE can learn model organization from software engineering For large systems, model organization is key for achieving Reusable model components Minimizing merging of modeling artifacts MBSE can learn effective approaches for configuration management of model components To facilitate good collaboration, configuration management of these model components is critical MBSE can learn effective design patterns / frameworks that allows for effective collaboration and reuse

Questions to be addressed with an MBSE Approach – (3) How should the practices and tools be integrated/coupled across disciplines? For large scale, complex designs the following areas need to be considered: Model Organization Number of Team Members Geographical distribution Configuration Management of model components Integration of tools Requirements Management tool Modeling tool Configuration Management tool Databases (that contain program specific data such as parameter values)

Questions to be addressed with an MBSE Approach – (4) How are the system, hardware, and software models managed to ensure an integrated technical baseline? To manage an MBSE effort of this scale the following topics would need to be addressed Program Management – Manage overall modeling activities across all disciplines Configuration Management – Manage the CM architecture to facilitate technical baselines, reuse components, distributed CM for collaboration Model Architecture – Manage the modeling structure and model organization to enable consistency and seamless integration between disciplines