System Engineering Models

Object Oriented Systems Modeling Formal Models Meta Model: The rules for making a model (example UML) Ontology: A set of model building blocks (the entities in a UML model for a database system) What is a formal model? A choice of Meta Model and Ontology determines a model space. Some guidelines for designing model spaces: Keep the rules simple Use many model spaces adapted to specific domains Use translation tools to move between domains "English Language" representation of OO models provides descriptive semantics. This mimics the way that we think about systems, but makes for long-winded descriptions of system structure. Diagraming notation provides a visual syntax that retains the formalism of the language, This makes models easier to capture, and understand. Standards such as UML provide a formal specification, called a meta-language, that secifies what constitutes a valid model description in a particular application domain. The standard also links the diagraming notation with the language representation. (In the case of UML the domain is software engineering) In the example presented in the next slide, the language supports three entities: classes, objects and relations. The language defines special relations between classes: generalization and aggregation, and a relationship between objects and classes, instantiation. It also specifies that interactions between objects are restricted to the relations that are defined for the classes that the objects represent. The specification of the formal modeling languages and ontologies for particular problem domains provides support for: Efficient storage and communication of all valid systems models Tools (such as requirements tracing tools) that can draw inferences about a model based rules that are founded in the model structure. Tools that can use mappings of ontologies to translate models from one domain to another, e.g. a mechanical system model to a thermal system model.