An Approach to Test Data Generation for Killing Multiple Mutants

  • Authors:

  • Ming-Hao Liu;You-Feng Gao;Jin-Hui Shan;Jiang-Hong Liu;Lu Zhang;Jia-Su Sun

  • Affiliations:

  • Peking University, Beijing, 100871, China;Peking University, Beijing, 100871, China;Peking University, Beijing, 100871, China;Peking University, Beijing, 100871, China;Peking University, Beijing, 100871, China;Peking University, Beijing, 100871, China

  • Venue:
  • ICSM '06 Proceedings of the 22nd IEEE International Conference on Software Maintenance
  • Year:
  • 2006

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Abstract

Software testing is an important technique for assurance of software quality. Mutation testing has been identified as a powerful fault-based technique for unit testing, and there has been some research on automatic generation of test data for mutation testing. However, existing approaches to this kind of test data generation usually generate test data according to one mutant at one time. Thus, more test data that are needed for achieving a given mutation score. In this paper, we propose a new approach to generating one test data according to multiple mutants that are mutated at the same location at one time. Thus, our approach can generate smaller test suite that can achieve the same mutation testing score. To evaluate our approach, we implemented a prototype tool based on our approach and carried out some preliminary experiments. The experimental results show that our approach is more cost-effective.