An Evaluation of a Test Scheduling Solution

Abstract

As recognized in the software engineering process, software testing during development is an aspect that must be improved to accurately predict and reduce probabilities of future software failures. A possible method of improving software reliability is to concentrate on the scheduling of the test process to reduce costs and increase coverage. Software test scheduling is the process of sequencing the test procedures to manage costs and maximize verification and validation of the system being evaluated. Changing the methodologies of software testing by implementing a scheduling process can affect many issues in software testing. Software testing is an evolutionary process; to be effective, the test scheduling problem and solution must be continuously revisited, revised and permitted to change according to the events as they occur. This implies that the test scheduling solution is dependant upon many factors, including software design model, results of previous test(s), and the time and resources available for further testing. This empirical study takes the testing information from a Published Specification and performs a detailed analysis of a scheduled solution. Based on the results of this work, it has been determined that the work and resources required to design and develop a software test schedule outweigh the resulting benefits.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1993
Accession Number
ADA264806

Entities

People

  • Timothy J. Kelly

Organizations

  • Naval Postgraduate School

Tags

DTIC Thesaurus Topics

  • Acceptance Tests
  • Classification
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Engineering
  • Reliability
  • Scheduling (Production)
  • Software Design
  • Software Development
  • Software Testing
  • Specifications
  • Test And Evaluation
  • Test Methods
  • Validation
  • Verification

Fields of Study

  • Computer science
  • Engineering

Readers

  • Operations Research
  • Software Engineering.
  • Theoretical Analysis.