An Examination of the Theoretical Foundations of the Object-Oriented Paradigm.

Abstract

The object-oriented paradigm provides a natural structure for describing and decomposing systems. The objectives of this research were to: provide a definition of an object model and consider its theoretical foundations; implement the defined object model to empirically investigate the concept; and implement a prototype environment to directly, interactively manipulate the object model. We define an object to have a unique identity and be composed of a set of attributes, a set of behaviors, and a set of (sub)objects. We define an attribute to be composed of an identifier, a value, and a set of attributes; and we define a behavior to be an identifier, a set of attributes, and a set of behaviors. We propose and prove the theorem that the defined object model can simulate a Turing machine. We then use the object-oriented design process to implement the defined object model under a prototype intractive environment called the HOOKE. We use the HOOKE to help build a simulation of a Turing machine under the defined object model, including several delta functions and input tapes. Thus we validate both the defined object model and the HOOKE. We conclude that the object-oriented paradigm rests on sound theoretical ground.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1988
Accession Number
ADA194879

Entities

People

  • William A. Bralick Jr

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Engineered Resilient Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Automata
  • Automata Theory
  • Classification
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Delta Functions
  • High Level Languages
  • Lisp Programming Language
  • Object Oriented Programming
  • Object-Oriented Programming Language
  • Programming Languages
  • Prototypes
  • Simulations
  • Software Development
  • System Software

Fields of Study

  • Computer science
  • Engineering

Readers

  • Computational Modeling and Simulation
  • Parallel and Distributed Computing.
  • Regression Analysis.