Skip to main content

An Automated Framework for Structural Test-data Generation

Tracey, Nigel J. and Clark, John A. and Mander, Keith C. and McDermid, John A. (1998) An Automated Framework for Structural Test-data Generation. In: Proceedings 13th IEEE International Conference on Automated Software Engineering. IEEE, pp. 285-288. ISBN 0-8186-8750-9. (doi:10.1109/ASE.1998.732680)

Abstract

Structural testing criteria are mandated in many software development standards and guidelines. The process of generating test data to achieve 100% coverage of a given structural coverage metric is labour-intensive and expensive. This paper presents an approach to automate the generation of such test data. The test-data generation is based on the application of a dynamic optimisation-based search for the required test data. The same approach can be generalised to solve other test-data generation problems. Three such applications are discussed-boundary value analysis, assertion/run-time exception testing, and component re-use testing. A prototype tool-set has been developed to facilitate the automatic generation of test data for these structural testing problems. The results of preliminary experiments using this technique and the prototype tool-set are presented and show the efficiency and effectiveness of this approach

Item Type: Book section
DOI/Identification number: 10.1109/ASE.1998.732680
Uncontrolled keywords: automatic testing; software testing; costs; application software; automation; simulated annealing; computer science; programming; software standards; standards development
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Faculties > Sciences > School of Computing > Systems Architecture Group
Depositing User: Mark Wheadon
Date Deposited: 24 Aug 2009 16:42 UTC
Last Modified: 06 Aug 2019 14:09 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/21595 (The current URI for this page, for reference purposes)
  • Depositors only (login required):

Downloads

Downloads per month over past year