Prioritized Constraints with Data Sampling Scores for Automatic Test Data Generation

  • Authors:

  • Xiao Ma;J. Jenny Li;David M. Weiss

  • Affiliations:

  • Avaya Labs Research;Avaya Labs Research;Avaya Labs Research

  • Venue:
  • SNPD '07 Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03
  • Year:
  • 2007

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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.