Of course, this is a simple model, but it actually runs which means that we can then verify that is correct and we can use it to support validation with the customer as well. We can examine different sequences of incoming events with different data values and look at the outcomes to confirm that they are what we expect.
 
Verifying the Requirements
For the verification of consistency of requirements, we must first decide what “inconsistent” means. I believe that inconsistent requirements manifest as incompatible outcomes in the same circumstance, such as when a traffic light would be Red because of one requirement but at the same time must also be Green to meet another. Since the execution of the requirements model has demonstrable outcomes, we can run the scenarios that represent the requirement and show through demonstration that all expected outcomes occur and that no undesired consequences arise. For the verification of completeness, we can first demonstrate – via trace links – that every requirement allocated to the use case is represented in at least one scenario as well as the normative state machine. Secondly, the precision of thought necessary to construct the model naturally raises questions during its creation. Have we considered what happens if the system is THIS state and then THAT occurs? What happens if THAT data is out of range? How quickly must THIS action occur? Have we created all of the scenarios and considered all of the operational variants? These questions will naturally occur to you as you construct the model and will result in the addition of new requirements or the correction of existing ones.

For correctness, I mean that the requirement specifies the proper outcome for a given situation. This is usually a combination of preconditions and a series of input-output event sequences resulting in a specified post-condition. With an executable use case model, we can show via test that for each situation, we have properly specified the output. We can do the same scenario with different data values to ensure that boundary values and potential singularities are properly addressed. We can change the execution order of incoming events to ensure that the specification properly handles all combinations of incoming events. Accuracy is a specific kind of correctness that has to do with quantitative outcomes rather than qualitative ones. For example, if the outcome is a control signal that is maintains an output that is proportional to an input (within an error range), we can run test cases to ensure that the specification actually achieves that. We can both execute the transformational logic in the requirements and formally (mathematically) analyze it as well if desired.

Be aware that this use case model is not the implementation. Even if the system use case model is functionally correct and executes properly, it is not operating on the desired delivery platform (hardware) and has not been optimized for cost, performance, reliability, safety, security, and other kinds of quality of service constraints. In fact, it has not been designed at all. All we’ve done is clearly and unambiguously state what a correctly designed system must do. This kind of model is known as a specification model and does not model the design.
 
Validating the Requirements
Validation refers to confirming that the system meets the needs of the customer. Systems that meet the requirements may fail to provide value to the customer because

• the customer specified the wrong thing,
• the requirements missed some aspect of correctness, completeness, accuracy or consistency,
• the requirements were captured incorrectly or ambiguously,
• the requirements, though correctly stated, were misunderstood

The nice thing about the executable requirements model is that you can demonstrate what you’ve specified to the customer, not as pile of dead trees to be read over a period of weeks but instead as a representation that supports exploration, experimentation, and confirmation. You may have stated what will happen if the physician flips this switch, turns that knob, and then pushes that button, but what if the physician pushes the button first? What has been specified in that case?  In a traditional requirements document, you’d have to search page by page looking for some indication as to what you specified would happen. With an executable requirements specification, you can simply say “I don’t know. Let’s try it and found out.” This means that the executable specification supports early validation of the requirements so that you can have a much higher confidence that the customer will be satisfied with the resulting product.
 
So does it really work?

I’ve consulted to hundreds of projects, almost all of which were in the “systems” space, such as aircraft, space craft, medical systems, telecommunications equipment, automobiles and the like. I’ve used this approach extensively with the Rational Rhapsody toolset for modeling and (usually) DOORS for managing the textual requirements. My personal experience is that it results in far higher quality in terms of requirements and a shorter development time with less rework and happier end customers. By way of a public example, I was involved in the development of the Eaton Hybrid Drivetrain project. We did this kind of use case functional analysis constructing executable use cases, and it identified many key requirements problems before they were discovered by downstream engineering. The resulting requirements specification was far more complete and correct after this work was done that in previous projects, meaning that the development team spent less time overall.

Summary
Building a set of requirements is both daunting and necessary. It is necessary because without it, projects will take longer – sometimes far longer – and cost more. Requirements defects are acknowledged to be the most expensive kind of defects because they are typically discovered late (when you’re supposed to be done) and require significant work to be thrown away and redone. It is a daunting task because text – while expressive – is ambiguous, vague and difficult to demonstrate its quality. However, by building executable requirements models, the quality of the requirements can be greatly improved at minimal cost and effort.
 
For more detail on the approach and specific techniques, you can find more information in my books Real-Time UML Workshop or Real-Time Agility