The deliverable “D1.2 Architecture specification and roadmap – initial version” has been released. In this deliverable we set the conceptual architecture of MegaM@rt, formalized the initial sets of requirements and described 35 baseline tools. This is a major milestone for the project helping us to build the new integrated framework based on our renowned tools.
MegaM@Rt wouldn’t be MegaM@Rt if we did not choose a model-driven approach for the Architecture deliverable. So, we set infrastructure on Modelio and Constellation to manage contributions of 53 architects of the project.
SOFTEAM set up the model templates for the contributions in requirements and tool architectures including the purpose requirements, functional interfaces, subordinates, deployment and relation to the framework.
Discussion on pro & cons, future work:
- Getting 53 people editing the same model was not that easy. We had to create guidelines and conduct multiple webinars to train experts about the modelling. The most time consuming was to distribute the licenses. Hopefully, we benefited from the ModelioSoft support.
- The model allowed us to see at once the common interfaces and deployment frameworks to identify good ways for integration.
- The project gladly accepted the model and the infrastructure for further work on the architecture of the individual tool sets constituting the MegaM@Rt framework with useful traceability links between Requirements->Framework->Tool sets->Individual tools.
- We can generate a set of multiple documents out of the model that will all be in sync with the architecture that understood in the same way by all the architects.
Bottom line:
- We collected important information about the tools: requirements, purpose, functionalities, interfaces.
- We taught project architects about common concepts and modelling guidelines and achieved common understanding.
- We obtained a live specification of 105 pages in one click.
- With more refinement we will enhance the specification and the document can be all re-generated at onces with the perfect coherence with the architecture.
- The model will be further exploited in the requirements elicitation, gap analysis and roadmap planning.
The work is ongoing. So, stay tuned.
Dr. Andrey Sadovykh (male) holds the M. Sc. degree in Applied Mathematics and Information Technologies of Moscow Institute of Physics and Technology, the Ph. D. degree in Computer Science of Paris 6th University and the MBA degree of HEC Paris Business School. For his Ph. D. he worked in EADS Space Transportation as a research engineer in development of systems for distributed monitoring and supervision. He was involved in the European Space Agency (ESA) projects for ATV spacecraft validation facilities and Hardware in the Loop simulation. In SOFTEAM, Dr. Sadovykh coordinates all the research activities of the company covering areas such as in model-driven development (MDD) and model-based system engineering (MBSE), Business Process Automation (BPA), eGovernment, eHealth, Cloud and Big Data. He worked as the project manager and the research engineer for the ENOSYS, MADES, PRESTO, MOMOCS, MODELPLEX, SHAPE, REMICS, JUNIPER, and ModaClouds projects. He was the technical coordinator in REMICS and MADES FP7 projects and was the consortium coordinator in the RTE Space (ESA-funded) and ENOSYS FP7 projects. In ModelWare project, Dr. Sadovykh lead development of middleware for integration of model-driven tools. In REMICS project, Dr. Sadovykh proposed an approach on model-driven migration of legacy systems to cloud infrastructures. Dr. Sadovykh is actively involved in the in the standardization activities at the Object Management Group. He contributed to standards on SOA and UI modelling – SoaML and IFML respectively. In ModelioSoft, SOFTEAM’s subsidiary, Dr. Sadovykh contributed to the marketing strategy and transformation to open source policies. Lately, in the frame of the MBA program at HEC Paris Business school, Dr. Sadovykh participated in consultancy project for CISCO Systems in the field of business strategy for “Value creation with Big Data at SMB market”.