Prioritized constraints with data sampling scores for automatic test data generation

Xiao Ma, J. Jenny Li, David M. Weiss

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Many automatic test data generation approaches use constraint solvers to find data values, e.g. the method given in [1]. One problem with this method is that it cannot generate test data when the constraints are not solvable, either because there is no solution or the constraints are too complex. We propose a constraint prioritization method using data sampling scores to generate valid test data even when a set of constraints is not solvable. Our case study illustrates the effectiveness of this method.

Original languageEnglish
Title of host publicationProceedings - SNPD 2007
Subtitle of host publicationEighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Pages1129-1134
Number of pages6
DOIs
StatePublished - 2007
EventSNPD 2007: 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Qingdao, China
Duration: 30 Jul 20071 Aug 2007

Publication series

NameProceedings - SNPD 2007: Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Volume3

Conference

ConferenceSNPD 2007: 8th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing
Country/TerritoryChina
CityQingdao
Period30/07/071/08/07

Keywords

  • Constraint solving
  • Software reliability
  • Test automation
  • Test case generation

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