Unified Modeling Language 2.0

Unified Modeling Language 2.0

Peter Fettke (Institute for Information Systems (IWi) at the DFKI, Germany)
DOI: 10.4018/978-1-60566-026-4.ch617
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Abstract

Mature engineering disciplines are generally characterized by accepted methodical standards for describing all relevant artifacts of their subject matter. Such standards not only enable practitioners to collaborate, but they also contribute to the development of the whole discipline. In 1994, Grady Booch, Jim Rumbaugh, and Ivar Jacobson joined together to unify the plethora of existing object-oriented systems engineering approaches at semantic and notation level (Booch, 2002; Fowler, 2004; Rumbaugh, Jacobson & Booch, 1998). Their effort leads to the unified modeling language (UML), a well-known, general-purpose, tool-supported, processindependent, and industry-standardized modeling language for visualizing, describing, specifying, and documenting systems artifacts.
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Background

The American Institute for Chartered Property Casualty Underwriters (CPCU) reports that the most common considerations found in automobile underwriting guidelines are:

  • age of operators;

  • age and type of automobile;

  • use of the automobile;

  • operator’s driving record;

  • territory;

  • gender;

  • marital status;

  • operator’s occupation;

  • operator’s personal characteristics; and

  • physical condition of the vehicle.

Traditionally, these comprise the core variables used in determining the acceptability, classifying, and rating of private passenger automobile insurance policies (Malecki and Underwriters, 1986).

Private passenger automobile insurance is well-suited for artificial intelligence applications applied to the underwriting function. There are three primary reasons for this:

  • there is a fixed set of finite data used to make the underwriting decision;

  • policies are highly standardized; and

  • deviations from the standard insurance contract are rare.

Key Terms in this Chapter

Conceptual Modeling: an action describing a domain with the help of a particular artificial or formalized language.

Reference Model: A reference model is a model representing a class of domains, e.g. a reference model for production planning and control systems. It is a conceptual framework or blueprint for system’s development.

Object-Oriented Analysis and Design (OOA & OOD): Software engineering approach to construct software systems by building object-oriented models that abstract key aspects of the target system.

Object-Oriented Programming (OOP): Object-oriented programming emphasizes the hiding or encapsulation of the inner state of objects and the specification of these objects by an interface. OOP languages support objects, classes and inheritance.

Model: A model is a particular product of conceptual modeling. It is a description of a domain using a particular language.

Methodology: A consistent and suited set of modeling methods providing procedures to apply the constructs of a modeling language.

Meta-Model: A meta-model is a model of model.

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