72,118 research outputs found

    A practical approach to object based requirements analysis

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    Presented here is an approach developed at the Unisys Houston Operation Division, which supports the early identification of objects. This domain oriented analysis and development concept is based on entity relationship modeling and object data flow diagrams. These modeling techniques, based on the GOOD methodology developed at the Goddard Space Flight Center, support the translation of requirements into objects which represent the real-world problem domain. The goal is to establish a solid foundation of understanding before design begins, thereby giving greater assurance that the system will do what is desired by the customer. The transition from requirements to object oriented design is also promoted by having requirements described in terms of objects. Presented is a five step process by which objects are identified from the requirements to create a problem definition model. This process involves establishing a base line requirements list from which an object data flow diagram can be created. Entity-relationship modeling is used to facilitate the identification of objects from the requirements. An example is given of how semantic modeling may be used to improve the entity-relationship model and a brief discussion on how this approach might be used in a large scale development effort

    An Object model for engineering design

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    Applications requiring sophisticated modeling techniques raise challenging issues to software designers. CAD/CAM and genetics are example of applications that call for powerful modeling techniques. Existing approaches seem limited in their ability to supports their demands. Relational database systems for example support only simple tables. The need to enhance their capabilities led to non-normalized relational data models. Object-oriented programming languages and databases propose new solutions to the problem of complex and composite object modeling and manipulation. Yet, severe shortcomings impede their practicability, e.g., their inability to model multiple object representations and complex semantic relationships. This paper is an informal overview of a data model called SHOOD implements sophisticated features, such as : o object persistence, multi-methods along a specific specialization hierarchy (which is independent of the class hierarchy), o sophisticated semantic relationships, e.g., dependency relationships between objects (which are totally independent of the composition relationship), o multiple object representations, allowing the users to manipulate the objects from several points of views simultaneously, o the systematic use of a powerful meta-object kernel, which is used to implement a reflexive architecture. The paper focuses on the last two issues

    Pattern Reification as the Basis for Description-Driven Systems

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    One of the main factors driving object-oriented software development for information systems is the requirement for systems to be tolerant to change. To address this issue in designing systems, this paper proposes a pattern-based, object-oriented, description-driven system (DDS) architecture as an extension to the standard UML four-layer meta-model. A DDS architecture is proposed in which aspects of both static and dynamic systems behavior can be captured via descriptive models and meta-models. The proposed architecture embodies four main elements - firstly, the adoption of a multi-layered meta-modeling architecture and reflective meta-level architecture, secondly the identification of four data modeling relationships that can be made explicit such that they can be modified dynamically, thirdly the identification of five design patterns which have emerged from practice and have proved essential in providing reusable building blocks for data management, and fourthly the encoding of the structural properties of the five design patterns by means of one fundamental pattern, the Graph pattern. A practical example of this philosophy, the CRISTAL project, is used to demonstrate the use of description-driven data objects to handle system evolution.Comment: 20 pages, 10 figure
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