Unveiling Models What’s about Model-Driven Approaches
نویسنده
چکیده
ions are correct or not. To be correct would mean to match all stakeholder understanding of the system, a particularly difficult task to concretize in an specification (model). It is important to notice that the problem we identify here is the fact that states the distinction among verification and validation activities in the testing discipline. To verify means to check whether the model satisfies its specification while to validate means to check whether it satisfies the stakeholders intent. Dimension conformation. We propose to conform this dimension in percentage of correctness, or any other discrete scale defined for the particular project. As a matter of convenience, we match the origin of the dimension to the most correct while the far-most point to the less correct. Localizing a model. A model can be placed at any point of this dimension, but exactly at one of them. The software development process must define several metrics to quantitatively determine the level of correctness of a model, and hence, to uniquely locate it at the corresponding point in this dimension. At the light of the previous discussion, specification models may be difficult to determine their correctness, mainly those corresponding to the higher levels of abstraction. The intuition of the responsible of those artifacts can be an approximative metric. Interesting points. The most interesting point in this dimension is the origin, corresponding to flawless models. However, testing techniques which do not apply formal methods for verification can seldom reach this level. Then, the best models are those which are nearest to the origin, being the final working system (hopefully) one of them. Model relationship. We can define a relationship to relate models through this dimension. Let’s consider a model Mi to be the input of the testing activity and as an output we determine a set of flaws in it. The change management discipline together with the responsible roles of Mi would determine the required changes and then perform them. An improved new version Mi+1 of Mi would be created which corrects (most of) the detected flaws. Then, we can state that Mi+1 corrects Mi as the former one is more correct than the latter. It is important to remark that a flaw in a model is due to one of two different causes: an error in the model or an error in the specification. In other words, a model can fail to satisfy its specification because it does not properly realizes its specification or because although it does realize its specification, such specification is not correctly expressed in the already built specification. Suppose we have model Mi and its specification model Si. When we detect a flaw in Mi then either Mi or Si are incorrect. To correct a model means either to update it or to update its specification. The first case is the one detailed above. The
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