Benefits of model-driven systems development

You can see how the situation progresses. Many restaurants now have someone to greet the customer, someone to seat them, someone to take their order, someone to pour beverages, someone to cook the order, someone to deliver it to the table, someone to deliver and collect the bill, someone to clear and set tables. The end goals remain the same, the tasks to be performed remain the same, but specialized roles are created to increase the restaurant’s capacity and throughput. However, as noted before, the increased capacity comes at a cost, both in increased salaries and increased management complexity—you now have quite a staff to manage. The cost must be balanced against the increased capacity.

Finally, as opposed to suffering through these options by painful experience and trial and error, you could model the various options and run simulations to learn what could happen and to better understand the implications of your options. You might save yourself a lot of pain, suffering, and the loss of your time and money. You would certainly be better informed about your options, and increased knowledge reduces uncertainty and risk.

MDSD provides ways to reason about these issues—both for systems and for business processes.

Scalability: Isomorphic composite structures and recursion

Systems are composite structures; that is, they are made up of distinct pieces. Not only are they composite structures, they are isomorphic;11 that is, each piece of the composite structure has a similar or identical structure itself. Composite isomorphic structures lend themselves to being processed recursively. MDSD is scalable because it is a recursive methodology. We can use it to reason about a system of any size. At each level of abstraction (or more precisely, at each model level, and at each level of decomposition)12 we perform basically the same activities: understand the context of the system under consideration, understand the collaboration required to achieve the system’s desired goals, and understand how function is distributed across form to achieve system goals within a set of constraints.