Economics 101: UML in Embedded Systems

With UML, just as with anything else in the embedded space, the ultimate criterion for success is the return on investment (ROI). Sure there are many factors at play, such as “coolness factor”, yearning for a “silver bullet” and truly “automatic programming” all fueled by the aggressive marketing rhetoric of tool vendors. But ultimately, to be successful, the benefits of a method must outweigh the learning curve, the cost of tools, the added maintenance costs, the hidden costs of “fighting the tool” and so on.

As it turns out, the ROI of UML is lousy unless the models are used to generate substantial portions of the production code. Without code generation, the models inevitably fall behind and become more of a liability than an asset. In this respect I tend to agree with the “UML Modeling Maturity Index (UMMI)“, invented by Bruce Douglass. According to the UMMI, without code generation UML can reach at most 30% of its potential, and this is assuming correct use of behavioral modeling. Without it, the benefits are below 10%. This is just too low to outweigh all the costs.

Unfortunately, code generation capabilities have been always associated with complex, expensive UML tools with a very steep learning curve and a price tag to match. With such a big investment side of the ROI equation, it’s quite difficult to reach sufficient return. Consequently, all too often big tools get abandoned and if they continue to be used at all, they end up as overpriced drawing packages.

So, to follow my purely economic argument, unless we make the investment part of the ROI equation low enough, without reducing the returns too much, UML has no chance. On the other hand, if we could achieve positive ROI (something like 80% of benefits for 10% of the cost), we would have a “game changer”.

To this end, when you look closer, the biggest “bang for the buck” in UML with respect to embedded code generation are: (1) hierarchical state machines (UML statecharts) and (2) an embedded real-time framework. Of course, these two ingredients work best together and complement each other. State machines can’t operate in vacuum and need an event-driven framework to provide execution context, thread-safe event passing, event queueing, etc. Framework benefits from state machines for structure and code generation capabilities.

I’m not sure if many people realize the critical importance of a framework, but a good framework is in many ways even more valuable than the tool itself, because the framework is the big enabler of architectural reuse, testability, traceability, and code generation to name just a few. The second component are state machines, but again I’m not sure if everybody realizes the importance of state nesting. Without support for state hierarchy, traditional “flat” state machines suffer from the phenomenon known as “state-transition explosion”, which renders them unusable for real-life problems.

As it turns out, the two critical ingredients for code generation can be had with much lower investment than traditionally thought. An event-driven, real-time framework can be no more complex as a traditional bare-bones RTOS (e.g., see the family of the open source QP frameworks). A UML modeling tool for creating hierarchical state machines and production code generation can be free and can be designed to minimize the problem of “fighting the tool” (e.g., see QM). Sure, you don’t get all the bells and whistles of IBM Rhapsody, but you get the arguably most valuable ingredients. More importantly, you have a chance to achieve a positive ROI on your first project. As I said, this to me is game changing.

Can a lightweight framework like QP and the QM modeling tool scale to really big projects? Well, I’ve seen it used for tens of KLOC-size projects by big, distributed teams and I haven’t seen any signs of over-stressing the architecture or the tool.

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