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  • 标题:Automatic Test Data Generation for Data-driven Testing using Abstract Test Script
  • 本地全文:下载
  • 作者:Jae-Han Cho ; Lee-Sub Lee
  • 期刊名称:International Journal of Software Engineering and Its Applications
  • 印刷版ISSN:1738-9984
  • 出版年度:2014
  • 卷号:8
  • 期号:12
  • 页码:153-164
  • DOI:10.14257/ijseia.2014.8.12.14
  • 出版社:SERSC
  • 摘要:In order to reduce the workload of generating test cases Data-driven testing was introduced. The method was proposed to solve the platform dependency of Record-and- playback. With Data-Driven testing, Testers could focus on generating test data itself so that it contributes to the improvement of productivity. Because a lot of testing data is required for better quality coverage, the workload of testers is explosively increased. In this paper, for efficient generation of test data, we propose the Abstract test script. The abstract test script provides various convenient operators for generating test data. With the Abstract test script, testers can design, implement and manage test data for Data-driven testing efficiently.
  • 关键词:Software Testing; Relational algebra; Data-driven testing; Testing algebra; ; Test driver; Boundary Partition; Class Design; Test Data Generation
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