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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 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. 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 multidisciplinary 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