A Finite Domain-Testing Strategy for Computer Program Testing.

Abstract

Program testing continues to be a practical approach to software validation, however the strategies currently being used lack a solid analytical foundation. The goal of this research is to analyze the program testing process, develop a strategy to maximize its effectiveness, and identify its limitations. A program can be viewed as a complex mapping from a N-dimensional space of input variables to an M-dimensional space of output variables. In the testing process the correctness of the program over a domain of this input space is inferred from its observed correctness on a small set of 'well-chosen' test values for that domain. The Domain Testing Strategy is used to determine the necessary set of test values and is shown to be successful for all types of errors except a small subclass called 'Missing Path Errors of Reduced Dimensionality'. The domain testing Strategy is developed for both continuous and discrete input spaces and for both linear and nonlinear predicates. The domain testing strategy is developed for both continuous and discrete input spaces and for both linear and nonlinear predicates. The only completely effective testing strategy is an exhaustive test which is totally impractical. The domain testing strategy offers a major reduction in the high cost of computer program testing with a minimal loss of testing effectiveness. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1977
Accession Number
ADA054771

Entities

People

  • Edward I. Cohen
  • Lee J. White

Organizations

  • Ohio State University

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Computations
  • Computer Programming
  • Computer Programs
  • Computers
  • Engineering
  • Information Science
  • Language
  • Programming Languages
  • Reliability
  • Security
  • Software Development
  • Standards
  • Test Methods
  • Two Dimensional
  • Validation

Fields of Study

  • Computer science
  • Engineering

Readers

  • Artificial Intelligence
  • Software Verification and Validation.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Space